The Data Science Course Complete Data Science Bootcamp 2025 Dec

The Data Science Course Complete Data Science Bootcamp 2025 Dec
     01. A Practical Example What You Will Learn in This Course.mp4 -


     01. A Practical Example What You Will Learn in This Course.vtt -


     02. What Does the Course Cover.mp4 -


     02. What Does the Course Cover.vtt -


     03. Download All Resources and Important FAQ.html -


     03. FAQ-The-Data-Science-Course.pdf -


     01. Data Science and Business Buzzwords Why are there so Many.mp4 -


     01. Data Science and Business Buzzwords Why are there so Many.vtt -


     02. What is the difference between Analysis and Analytics.mp4 -


     02. What is the difference between Analysis and Analytics.vtt -


     03. Business Analytics, Data Analytics, and Data Science An Introduction.mp4 -


     03. Business Analytics, Data Analytics, and Data Science An Introduction.vtt -


     04. Continuing with BI, ML, and AI.mp4 -


     04. Continuing with BI, ML, and AI.vtt -


     05. Traditional AI vs. Generative AI.mp4 -


     05. Traditional AI vs. Generative AI.vtt -


     06. More Examples of Generative AI.mp4 -


     06. More Examples of Generative AI.vtt -


     07. A Breakdown of our Data Science Infographic.mp4 -


     07. A Breakdown of our Data Science Infographic.vtt -


     03. 365-DataScience-Diagram.pdf -


     04. 365-DataScience-Diagram.pdf -


     04. 365-DataScience.png -


     07. 365-DataScience.png -


     01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4 -


     01. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.vtt -


     01. The Reason Behind These Disciplines.mp4 -


     01. The Reason Behind These Disciplines.vtt -


     01. Techniques for Working with Traditional Data.mp4 -


     01. Techniques for Working with Traditional Data.vtt -


     02. Real Life Examples of Traditional Data.mp4 -


     02. Real Life Examples of Traditional Data.vtt -


     03. Techniques for Working with Big Data.mp4 -


     03. Techniques for Working with Big Data.vtt -


     04. Real Life Examples of Big Data.mp4 -


     04. Real Life Examples of Big Data.vtt -


     05. Business Intelligence (BI) Techniques.mp4 -


     05. Business Intelligence (BI) Techniques.vtt -


     06. Real Life Examples of Business Intelligence (BI).mp4 -


     06. Real Life Examples of Business Intelligence (BI).vtt -


     07. Techniques for Working with Traditional Methods.mp4 -


     07. Techniques for Working with Traditional Methods.vtt -


     08. Real Life Examples of Traditional Methods.mp4 -


     08. Real Life Examples of Traditional Methods.vtt -


     09. Machine Learning (ML) Techniques.mp4 -


     09. Machine Learning (ML) Techniques.vtt -


     10. Types of Machine Learning.mp4 -


     10. Types of Machine Learning.vtt -


     11. Evolution and Latest Trends of Machine Learning (ML).mp4 -


     11. Evolution and Latest Trends of Machine Learning (ML).vtt -


     12. Real Life Examples of Machine Learning (ML).mp4 -


     12. Real Life Examples of Machine Learning (ML).vtt -


     01. Necessary Programming Languages and Software Used in Data Science.mp4 -


     01. Necessary Programming Languages and Software Used in Data Science.vtt -


     01. Finding the Job - What to Expect and What to Look for.mp4 -


     01. Finding the Job - What to Expect and What to Look for.vtt -


     01. Debunking Common Misconceptions.mp4 -


     01. Debunking Common Misconceptions.vtt -


     01. The Basic Probability Formula.mp4 -


     01. The Basic Probability Formula.vtt -


     02. Computing Expected Values.mp4 -


     02. Computing Expected Values.vtt -


     03. Frequency.mp4 -


     03. Frequency.vtt -


     04. Events and Their Complements.mp4 -


     04. Events and Their Complements.vtt -


     01. Course-Notes-Basic-Probability.pdf -


     01. Fundamentals of Combinatorics.mp4 -


     01. Fundamentals of Combinatorics.vtt -


     02. Permutations and How to Use Them.mp4 -


     02. Permutations and How to Use Them.vtt -


     03. Simple Operations with Factorials.mp4 -


     03. Simple Operations with Factorials.vtt -


     04. Solving Variations with Repetition.mp4 -


     04. Solving Variations with Repetition.vtt -


     05. Solving Variations without Repetition.mp4 -


     05. Solving Variations without Repetition.vtt -


     06. Solving Combinations.mp4 -


     06. Solving Combinations.vtt -


     07. Symmetry of Combinations.mp4 -


     07. Symmetry of Combinations.vtt -


     08. Solving Combinations with Separate Sample Spaces.mp4 -


     08. Solving Combinations with Separate Sample Spaces.vtt -


     09. Combinatorics in Real-Life The Lottery.mp4 -


     09. Combinatorics in Real-Life The Lottery.vtt -


     10. A Recap of Combinatorics.mp4 -


     10. A Recap of Combinatorics.vtt -


     11. A Practical Example of Combinatorics.mp4 -


     11. A Practical Example of Combinatorics.vtt -


     01. Course-Notes-Combinatorics.pdf -


     06. Combinations-With-Repetition.pdf -


     07. Symmetry-Explained.pdf -


     11. Additional-Exercises-Combinatorics-Solutions.pdf -


     11. Additional-Exercises-Combinatorics.pdf -


     01. Sets and Events.mp4 -


     01. Sets and Events.vtt -


     02. Ways Sets Can Interact.mp4 -


     02. Ways Sets Can Interact.vtt -


     03. Intersection of Sets.mp4 -


     03. Intersection of Sets.vtt -


     04. Union of Sets.mp4 -


     04. Union of Sets.vtt -


     05. Mutually Exclusive Sets.mp4 -


     05. Mutually Exclusive Sets.vtt -


     06. Dependence and Independence of Sets.mp4 -


     06. Dependence and Independence of Sets.vtt -


     07. The Conditional Probability Formula.mp4 -


     07. The Conditional Probability Formula.vtt -


     08. The Law of Total Probability.mp4 -


     08. The Law of Total Probability.vtt -


     09. The Additive Rule.mp4 -


     09. The Additive Rule.vtt -


     10. The Multiplication Law.mp4 -


     10. The Multiplication Law.vtt -


     11. Bayes' Law.mp4 -


     11. Bayes' Law.vtt -


     12. A Practical Example of Bayesian Inference.mp4 -


     12. A Practical Example of Bayesian Inference.vtt -


     01. Course-Notes-Bayesian-Inference.pdf -


     12. Bayesian-Homework-Solutions.pdf -


     12. Bayesian-Homework.pdf -


     12. CDS-2017-2018-Hamilton.pdf -


     01. Fundamentals of Probability Distributions.mp4 -


     01. Fundamentals of Probability Distributions.vtt -


     02. Types of Probability Distributions.mp4 -


     02. Types of Probability Distributions.vtt -


     03. Characteristics of Discrete Distributions.mp4 -


     03. Characteristics of Discrete Distributions.vtt -


     04. Discrete Distributions The Uniform Distribution.mp4 -


     04. Discrete Distributions The Uniform Distribution.vtt -


     05. Discrete Distributions The Bernoulli Distribution.mp4 -


     05. Discrete Distributions The Bernoulli Distribution.vtt -


     06. Discrete Distributions The Binomial Distribution.mp4 -


     06. Discrete Distributions The Binomial Distribution.vtt -


     07. Discrete Distributions The Poisson Distribution.mp4 -


     07. Discrete Distributions The Poisson Distribution.vtt -


     08. Characteristics of Continuous Distributions.mp4 -


     08. Characteristics of Continuous Distributions.vtt -


     09. Continuous Distributions The Normal Distribution.mp4 -


     09. Continuous Distributions The Normal Distribution.vtt -


     10. Continuous Distributions The Standard Normal Distribution.mp4 -


     10. Continuous Distributions The Standard Normal Distribution.vtt -


     11. Continuous Distributions The Students' T Distribution.mp4 -


     11. Continuous Distributions The Students' T Distribution.vtt -


     12. Continuous Distributions The Chi-Squared Distribution.mp4 -


     12. Continuous Distributions The Chi-Squared Distribution.vtt -


     13. Continuous Distributions The Exponential Distribution.mp4 -


     13. Continuous Distributions The Exponential Distribution.vtt -


     14. Continuous Distributions The Logistic Distribution.mp4 -


     14. Continuous Distributions The Logistic Distribution.vtt -


     15. A Practical Example of Probability Distributions.mp4 -


     15. A Practical Example of Probability Distributions.vtt -


     01. Course-Notes-Probability-Distributions.pdf -


     07. Poisson-Expected-Value-and-Variance.pdf -


     08. Solving-Integrals.pdf -


     09. Normal-Distribution-Exp-and-Var.pdf -


     15. Customers-Membership-post.xlsx -


     15. Customers-Membership.xlsx -


     15. Daily-Views-post.xlsx -


     15. Daily-Views.xlsx -


     15. FIFA19-post.csv -


     15. FIFA19.csv -


     01. Probability in Finance.mp4 -


     01. Probability in Finance.vtt -


     02. Probability in Statistics.mp4 -


     02. Probability in Statistics.vtt -


     03. Probability in Data Science.mp4 -


     03. Probability in Data Science.vtt -


     01. Probability-in-Finance-Homework.pdf -


     01. Probability-in-Finance-Solutions.pdf -


     03. Probability-Cheat-Sheet.pdf -


     01. Population and Sample.mp4 -


     01. Population and Sample.vtt -


     01. Course-notes-descriptive-statistics.pdf -


     01. Statistics-Glossary.xlsx -


     01. Types of Data.mp4 -


     01. Types of Data.vtt -


     02. Levels of Measurement.mp4 -


     02. Levels of Measurement.vtt -


     03. Categorical Variables - Visualization Techniques.mp4 -


     03. Categorical Variables - Visualization Techniques.vtt -


     04. Categorical Variables Exercise.html -


     05. Numerical Variables - Frequency Distribution Table.mp4 -


     05. Numerical Variables - Frequency Distribution Table.vtt -


     06. Numerical Variables Exercise.html -


     07. The Histogram.mp4 -


     07. The Histogram.vtt -


     08. Histogram Exercise.html -


     09. Cross Tables and Scatter Plots.mp4 -


     09. Cross Tables and Scatter Plots.vtt -


     10. Cross Tables and Scatter Plots Exercise.html -


     11. Mean, median and mode.mp4 -


     11. Mean, median and mode.vtt -


     12. Mean, Median and Mode Exercise.html -


     13. Skewness.mp4 -


     13. Skewness.vtt -


     14. Skewness Exercise.html -


     15. Variance.mp4 -


     15. Variance.vtt -


     16. Variance Exercise.html -


     17. Standard Deviation and Coefficient of Variation.mp4 -


     17. Standard Deviation and Coefficient of Variation.vtt -


     18. Standard Deviation and Coefficient of Variation Exercise.html -


     19. Covariance.mp4 -


     19. Covariance.vtt -


     20. Covariance Exercise.html -


     21. Correlation Coefficient.mp4 -


     21. Correlation Coefficient.vtt -


     22. Correlation Coefficient Exercise.html -


     01. Course-notes-descriptive-statistics.pdf -


     01. Glossary.xlsx -


     03. 2.3.Categorical-variables.Visualization-techniques-lesson.xlsx -


     04. 2.3.Categorical-variables.Visualization-techniques-exercise-solution.xlsx -


     04. 2.3.Categorical-variables.Visualization-techniques-exercise.xlsx -


     04. Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf -


     05. 2.4.Numerical-variables.Frequency-distribution-table-lesson.xlsx -


     06. 2.4.Numerical-variables.Frequency-distribution-table-exercise-solution.xlsx -


     07. 2.5.The-Histogram-lesson.xlsx -


     08. 2.5.The-Histogram-exercise-solution.xlsx -


     08. 2.5.The-Histogram-exercise.xlsx -


     08. Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf -


     09. 2.6.Cross-table-and-scatter-plot.xlsx -


     10. 2.6.Cross-table-and-scatter-plot-exercise-solution.xlsx -


     10. 2.6.Cross-table-and-scatter-plot-exercise.xlsx -


     11. 2.7.Mean-median-and-mode-lesson.xlsx -


     12. 2.7.Mean-median-and-mode-exercise-solution.xlsx -


     12. 2.7.Mean-median-and-mode-exercise.xlsx -


     13. 2.8.Skewness-lesson.xlsx -


     14. 2.8.Skewness-exercise-solution.xlsx -


     14. 2.8.Skewness-exercise.xlsx -


     15. 2.9.Variance-lesson.xlsx -


     16. 2.9.Variance-exercise-solution.xlsx -


     16. 2.9.Variance-exercise.xlsx -


     17. 2.10.Standard-deviation-and-coefficient-of-variation-lesson.xlsx -


     18. 2.10.Standard-deviation-and-coefficient-of-variation-exercise-solution.xlsx -


     18. 2.10.Standard-deviation-and-coefficient-of-variation-exercise.xlsx -


     19. 2.11.Covariance-lesson.xlsx -


     20. 2.11.Covariance-exercise-solution.xlsx -


     20. 2.11.Covariance-exercise.xlsx -


     22. 2.12.Correlation-exercise-solution.xlsx -


     22. 2.12.Correlation-exercise.xlsx -


     01. Practical Example Descriptive Statistics.mp4 -


     01. Practical Example Descriptive Statistics.vtt -


     02. Practical Example Descriptive Statistics Exercise.html -


     01. 2.13.Practical-example.Descriptive-statistics-lesson.xlsx -


     02. 2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx -


     02. 2.13.Practical-example.Descriptive-statistics-exercise.xlsx -


     01. Introduction.mp4 -


     01. Introduction.vtt -


     02. What is a Distribution.mp4 -


     02. What is a Distribution.vtt -


     03. The Normal Distribution.mp4 -


     03. The Normal Distribution.vtt -


     04. The Standard Normal Distribution.mp4 -


     04. The Standard Normal Distribution.vtt -


     05. The Standard Normal Distribution Exercise.html -


     06. Central Limit Theorem.mp4 -


     06. Central Limit Theorem.vtt -


     07. Standard error.mp4 -


     07. Standard error.vtt -


     08. Estimators and Estimates.mp4 -


     08. Estimators and Estimates.vtt -


     01. Course-notes-inferential-statistics.pdf -


     02. 3.2.What-is-a-distribution-lesson.xlsx -


     02. Course-notes-inferential-statistics.pdf -


     04. 3.4.Standard-normal-distribution-lesson.xlsx -


     05. 3.4.Standard-normal-distribution-exercise-solution.xlsx -


     05. 3.4.Standard-normal-distribution-exercise.xlsx -


     01. What are Confidence Intervals.mp4 -


     01. What are Confidence Intervals.vtt -


     02. Confidence Intervals; Population Variance Known; Z-score.mp4 -


     02. Confidence Intervals; Population Variance Known; Z-score.vtt -


     03. Confidence Intervals; Population Variance Known; Z-score; Exercise.html -


     04. Confidence Interval Clarifications.mp4 -


     04. Confidence Interval Clarifications.vtt -


     05. Student's T Distribution.mp4 -


     05. Student's T Distribution.vtt -


     06. Confidence Intervals; Population Variance Unknown; T-score.mp4 -


     06. Confidence Intervals; Population Variance Unknown; T-score.vtt -


     07. Confidence Intervals; Population Variance Unknown; T-score; Exercise.html -


     08. Margin of Error.mp4 -


     08. Margin of Error.vtt -


     09. Confidence intervals. Two means. Dependent samples.mp4 -


     09. Confidence intervals. Two means. Dependent samples.vtt -


     10. Confidence intervals. Two means. Dependent samples Exercise.html -


     11. Confidence intervals. Two means. Independent Samples (Part 1).mp4 -


     11. Confidence intervals. Two means. Independent Samples (Part 1).vtt -


     12. Confidence intervals. Two means. Independent Samples (Part 1). Exercise.html -


     13. Confidence intervals. Two means. Independent Samples (Part 2).mp4 -


     13. Confidence intervals. Two means. Independent Samples (Part 2).vtt -


     14. Confidence intervals. Two means. Independent Samples (Part 2). Exercise.html -


     15. Confidence intervals. Two means. Independent Samples (Part 3).mp4 -


     15. Confidence intervals. Two means. Independent Samples (Part 3).vtt -


     02. 3.9.Population-variance-known-z-score-lesson.xlsx -


     02. 3.9.The-z-table.xlsx -


     03. 3.9.Population-variance-known-z-score-exercise-solution.xlsx -


     03. 3.9.Population-variance-known-z-score-exercise.xlsx -


     03. 3.9.The-z-table.xlsx -


     06. 3.11.Population-variance-unknown-t-score-lesson.xlsx -


     06. 3.11.The-t-table.xlsx -


     07. 3.11.Population-variance-unknown-t-score-exercise-solution.xlsx -


     07. 3.11.Population-variance-unknown-t-score-exercise.xlsx -


     07. 3.11.The-t-table.xlsx -


     09. 3.13.Confidence-intervals.Two-means.Dependent-samples-lesson.xlsx -


     10. 3.13.Confidence-intervals.Two-means.Dependent-samples-exercise-solution.xlsx -


     10. 3.13.Confidence-intervals.Two-means.Dependent-samples-exercise.xlsx -


     11. 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-lesson.xlsx -


     12. 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise-solution.xlsx -


     12. 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise.xlsx -


     13. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-lesson.xlsx -


     14. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise-solution.xlsx -


     14. 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise.xlsx -


     01. Practical Example Inferential Statistics.mp4 -


     01. Practical Example Inferential Statistics.vtt -


     02. Practical Example Inferential Statistics Exercise.html -


     01. 3.17.Practical-example.Confidence-intervals-lesson.xlsx -


     02. 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx -


     02. 3.17.Practical-example.Confidence-intervals-exercise.xlsx -


     01. Null vs Alternative Hypothesis.mp4 -


     01. Null vs Alternative Hypothesis.vtt -


     02. Further Reading on Null and Alternative Hypothesis.html -


     03. Rejection Region and Significance Level.mp4 -


     03. Rejection Region and Significance Level.vtt -


     04. Type I Error and Type II Error.mp4 -


     04. Type I Error and Type II Error.vtt -


     05. Test for the Mean. Population Variance Known.mp4 -


     05. Test for the Mean. Population Variance Known.vtt -


     06. Test for the Mean. Population Variance Known Exercise.html -


     07. p-value.mp4 -


     07. p-value.vtt -


     08. Test for the Mean. Population Variance Unknown.mp4 -


     08. Test for the Mean. Population Variance Unknown.vtt -


     09. Test for the Mean. Population Variance Unknown Exercise.html -


     10. Test for the Mean. Dependent Samples.mp4 -


     10. Test for the Mean. Dependent Samples.vtt -


     11. Test for the Mean. Dependent Samples Exercise.html -


     12. Test for the mean. Independent Samples (Part 1).mp4 -


     12. Test for the mean. Independent Samples (Part 1).vtt -


     13. Test for the mean. Independent Samples (Part 1). Exercise.html -


     14. Test for the mean. Independent Samples (Part 2).mp4 -


     14. Test for the mean. Independent Samples (Part 2).vtt -


     15. Test for the mean. Independent Samples (Part 2). Exercise.html -


     01. Course-notes-hypothesis-testing.pdf -


     03. Course-notes-hypothesis-testing.pdf -


     05. 4.4.Test-for-the-mean.Population-variance-known-lesson.xlsx -


     06. 4.4.Test-for-the-mean.Population-variance-known-exercise-solution.xlsx -


     06. 4.4.Test-for-the-mean.Population-variance-known-exercise.xlsx -


     07. Online-p-value-calculator.pdf -


     08. 4.6.Test-for-the-mean.Population-variance-unknown-lesson.xlsx -


     09. 4.6.Test-for-the-mean.Population-variance-unknown-exercise-solution.xlsx -


     09. 4.6.Test-for-the-mean.Population-variance-unknown-exercise.xlsx -


     10. 4.7.Test-for-the-mean.Dependent-samples-lesson.xlsx -


     11. 4.7.Test-for-the-mean.Dependent-samples-exercise-solution.xlsx -


     11. 4.7.Test-for-the-mean.Dependent-samples-exercise.xlsx -


     12. 4.8.Test-for-the-mean.Independent-samples-Part-1-lesson.xlsx -


     13. 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise-solution.xlsx -


     13. 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise.xlsx -


     14. 4.9.Test-for-the-mean.Independent-samples-Part-2-lesson.xlsx -


     15. 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx -


     15. 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx -


     01. Practical Example Hypothesis Testing.mp4 -


     01. Practical Example Hypothesis Testing.vtt -


     02. Practical Example Hypothesis Testing Exercise.html -


     01. 4.10.Hypothesis-testing-section-practical-example.xlsx -


     02. 4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx -


     02. 4.10.Hypothesis-testing-section-practical-example-exercise.xlsx -


     01. Introduction to Programming.mp4 -


     01. Introduction to Programming.vtt -


     02. Why Python.mp4 -


     02. Why Python.vtt -


     03. Why Jupyter.mp4 -


     03. Why Jupyter.vtt -


     04. Installing Python and Jupyter.mp4 -


     04. Installing Python and Jupyter.vtt -


     05. Understanding Jupyter's Interface - the Notebook Dashboard.mp4 -


     05. Understanding Jupyter's Interface - the Notebook Dashboard.vtt -


     06. Prerequisites for Coding in the Jupyter Notebooks.mp4 -


     06. Prerequisites for Coding in the Jupyter Notebooks.vtt -


     01. Introduction-to-Python-Course-Notes.pdf -


     01. Variables.mp4 -


     01. Variables.vtt -


     02. Numbers and Boolean Values in Python.mp4 -


     02. Numbers and Boolean Values in Python.vtt -


     03. Python Strings.mp4 -


     03. Python Strings.vtt -


     01. Introduction-to-Python-Course-Notes.pdf -


     01. Variables-Exercise-Py3.ipynb -


     01. Variables-Lecture-Py3.ipynb -


     01. Variables-Solution-Py3.ipynb -


     02. Numbers-and-Boolean-Values-Exercise-Py3.ipynb -


     02. Numbers-and-Boolean-Values-Lecture-Py3.ipynb -


     02. Numbers-and-Boolean-Values-Solution-Py3.ipynb -


     03. Strings-Exercise-Py3.ipynb -


     03. Strings-Lecture-Py3.ipynb -


     03. Strings-Solution-Py3.ipynb -


     01. Using Arithmetic Operators in Python.mp4 -


     01. Using Arithmetic Operators in Python.vtt -


     02. The Double Equality Sign.mp4 -


     02. The Double Equality Sign.vtt -


     03. How to Reassign Values.mp4 -


     03. How to Reassign Values.vtt -


     04. Add Comments.mp4 -


     04. Add Comments.vtt -


     05. Understanding Line Continuation.mp4 -


     05. Understanding Line Continuation.vtt -


     06. Indexing Elements.mp4 -


     06. Indexing Elements.vtt -


     07. Structuring with Indentation.mp4 -


     07. Structuring with Indentation.vtt -


     01. Arithmetic-Operators-Exercise-Py3.ipynb -


     01. Arithmetic-Operators-Lecture-Py3.ipynb -


     01. Arithmetic-Operators-Solution-Py3.ipynb -


     02. The-Double-Equality-Sign-Exercise-Py3.ipynb -


     02. The-Double-Equality-Sign-Lecture-Py3.ipynb -


     02. The-Double-Equality-Sign-Solution-Py3.ipynb -


     03. Reassign-Values-Exercise-Py3.ipynb -


     03. Reassign-Values-Lecture-Py3.ipynb -


     03. Reassign-Values-Solution-Py3.ipynb -


     04. Add-Comments-Lecture-Py3.ipynb -


     05. Line-Continuation-Exercise-Py3.ipynb -


     05. Line-Continuation-Lecture-Py3.ipynb -


     05. Line-Continuation-Solution-Py3.ipynb -


     06. Indexing-Elements-Exercise-Py3.ipynb -


     06. Indexing-Elements-Lecture-Py3.ipynb -


     06. Indexing-Elements-Solution-Py3.ipynb -


     07. Structure-Your-Code-with-Indentation-Exercise-Py3.ipynb -


     07. Structure-Your-Code-with-Indentation-Lecture-Py3.ipynb -


     07. Structure-Your-Code-with-Indentation-Solution-Py3.ipynb -


     01. Comparison Operators.mp4 -


     01. Comparison Operators.vtt -


     02. Logical and Identity Operators.mp4 -


     02. Logical and Identity Operators.vtt -


     01. Comparison-Operators-Exercise-Py3.ipynb -


     01. Comparison-Operators-Lecture-Py3.ipynb -


     01. Comparison-Operators-Solution-Py3.ipynb -


     02. Logical-and-Identity-Operators-Lecture-Py3.ipynb -


     02. Logical-and-Identity-Operators-Solution-Py3.ipynb -


     01. The IF Statement.mp4 -


     01. The IF Statement.vtt -


     02. The ELSE Statement.mp4 -


     02. The ELSE Statement.vtt -


     03. The ELIF Statement.mp4 -


     03. The ELIF Statement.vtt -


     04. A Note on Boolean Values.mp4 -


     04. A Note on Boolean Values.vtt -


     01. Introduction-to-the-If-Statement-Exercise-Py3.ipynb -


     01. Introduction-to-the-If-Statement-Lecture-Py3.ipynb -


     01. Introduction-to-the-If-Statement-Solution-Py3.ipynb -


     02. Add-an-Else-Statement-Exercise-Py3.ipynb -


     02. Add-an-Else-Statement-Lecture-Py3.ipynb -


     02. Add-an-Else-Statement-Solution-Py3.ipynb -


     03. Else-If-for-Brief-Elif-Exercise-Py3.ipynb -


     03. Else-If-for-Brief-Elif-Lecture-Py3.ipynb -


     03. Else-If-for-Brief-Elif-Solution-Py3.ipynb -


     04. A-Note-on-Boolean-Values-Lecture-Py3.ipynb -


     01. Defining a Function in Python.mp4 -


     01. Defining a Function in Python.vtt -


     02. How to Create a Function with a Parameter.mp4 -


     02. How to Create a Function with a Parameter.vtt -


     03. Defining a Function in Python - Part II.mp4 -


     03. Defining a Function in Python - Part II.vtt -


     04. How to Use a Function within a Function.mp4 -


     04. How to Use a Function within a Function.vtt -


     05. Conditional Statements and Functions.mp4 -


     05. Conditional Statements and Functions.vtt -


     06. Functions Containing a Few Arguments.mp4 -


     06. Functions Containing a Few Arguments.vtt -


     07. Built-in Functions in Python.mp4 -


     07. Built-in Functions in Python.vtt -


     01. Defining-a-Function-in-Python-Lecture-Py3.ipynb -


     02. Creating-a-Function-with-a-Parameter-Exercise-Py3.ipynb -


     02. Creating-a-Function-with-a-Parameter-Lecture-Py3.ipynb -


     02. Creating-a-Function-with-a-Parameter-Solution-Py3.ipynb -


     03. Another-Way-to-Define-a-Function-Exercise-Py3.ipynb -


     03. Another-Way-to-Define-a-Function-Lecture-Py3.ipynb -


     03. Another-Way-to-Define-a-Function-Solution-Py3.ipynb -


     04. 0.6.4-Using-a-Function-in-another-Function-Exercise-Py3.ipynb -


     04. 0.6.4-Using-a-Function-in-another-Function-Lecture-Py3.ipynb -


     04. 0.6.4-Using-a-Function-in-another-Function-Solution-Py3.ipynb -


     05. Combining-Conditional-Statements-and-Functions-Exercise-Py3.ipynb -


     05. Combining-Conditional-Statements-and-Functions-Lecture-Py3.ipynb -


     05. Combining-Conditional-Statements-and-Functions-Solution-Py3.ipynb -


     06. Creating-Functions-Containing-a-Few-Arguments-Lecture-Py3.ipynb -


     07. Notable-Built-In-Functions-in-Python-Exercise-Py3.ipynb -


     07. Notable-Built-In-Functions-in-Python-Lecture-Py3.ipynb -


     07. Notable-Built-In-Functions-in-Python-Solution-Py3.ipynb -


     01. Lists.mp4 -


     01. Lists.vtt -


     02. Using Methods.mp4 -


     02. Using Methods.vtt -


     03. List Slicing.mp4 -


     03. List Slicing.vtt -


     04. Tuples.mp4 -


     04. Tuples.vtt -


     05. Dictionaries.mp4 -


     05. Dictionaries.vtt -


     01. Lists-Exercise-Py3.ipynb -


     01. Lists-Lecture-Py3.ipynb -


     01. Lists-Solution-Py3.ipynb -


     02. Help-Yourself-with-Methods-Exercise-Py3.ipynb -


     02. Help-Yourself-with-Methods-Lecture-Py3.ipynb -


     02. Help-Yourself-with-Methods-Solution-Py3.ipynb -


     03. List-Slicing-Exercise-Py3.ipynb -


     03. List-Slicing-Lecture-Py3.ipynb -


     03. List-Slicing-Solution-Py3.ipynb -


     04. Tuples-Exercise-Py3.ipynb -


     04. Tuples-Lecture-Py3.ipynb -


     04. Tuples-Solution-Py3.ipynb -


     05. Dictionaries-Exercise-Py3.ipynb -


     05. Dictionaries-Lecture-Py3.ipynb -


     05. Dictionaries-Solution-Py3.ipynb -


     01. For Loops.mp4 -


     01. For Loops.vtt -


     02. While Loops and Incrementing.mp4 -


     02. While Loops and Incrementing.vtt -


     03. Lists with the range() Function.mp4 -


     03. Lists with the range() Function.vtt -


     04. Conditional Statements and Loops.mp4 -


     04. Conditional Statements and Loops.vtt -


     05. Conditional Statements, Functions, and Loops.mp4 -


     05. Conditional Statements, Functions, and Loops.vtt -


     06. How to Iterate over Dictionaries.mp4 -


     06. How to Iterate over Dictionaries.vtt -


     01. For-Loops-Exercise-Py3.ipynb -


     01. For-Loops-Lecture-Py3.ipynb -


     01. For-Loops-Solution-Py3.ipynb -


     02. While-Loops-and-Incrementing-Exercise-Py3.ipynb -


     02. While-Loops-and-Incrementing-Lecture-Py3.ipynb -


     02. While-Loops-and-Incrementing-Solution-Py3.ipynb -


     03. Create-Lists-with-the-range-Function-Exercise-Py3.ipynb -


     03. Create-Lists-with-the-range-Function-Lecture-Py3.ipynb -


     03. Create-Lists-with-the-range-Function-Solution-Py3.ipynb -


     04. Use-Conditional-Statements-and-Loops-Together-Exercise-Py3.ipynb -


     04. Use-Conditional-Statements-and-Loops-Together-Lecture-Py3.ipynb -


     04. Use-Conditional-Statements-and-Loops-Together-Solution-Py3.ipynb -


     05. All-In-Exercise-Py3.ipynb -


     05. All-In-Lecture-Py3.ipynb -


     05. All-In-Solution-Py3.ipynb -


     06. Iterating-over-Dictionaries-Exercise-Py3.ipynb -


     06. Iterating-over-Dictionaries-Lecture-Py3.ipynb -


     06. Iterating-over-Dictionaries-Solution-Py3.ipynb -


     01. Object Oriented Programming.mp4 -


     01. Object Oriented Programming.vtt -


     02. Modules and Packages.mp4 -


     02. Modules and Packages.vtt -


     03. What is the Standard Library.mp4 -


     03. What is the Standard Library.vtt -


     04. Importing Modules in Python.mp4 -


     04. Importing Modules in Python.vtt -


     01. Introduction to Regression Analysis.mp4 -


     01. Introduction to Regression Analysis.vtt -


     01. Course-notes-regression-analysis.pdf -


     01. The Linear Regression Model.mp4 -


     01. The Linear Regression Model.vtt -


     02. Correlation vs Regression.mp4 -


     02. Correlation vs Regression.vtt -


     03. Geometrical Representation of the Linear Regression Model.mp4 -


     03. Geometrical Representation of the Linear Regression Model.vtt -


     04. Python Packages Installation.mp4 -


     04. Python Packages Installation.vtt -


     05. First Regression in Python.mp4 -


     05. First Regression in Python.vtt -


     06. First Regression in Python Exercise.html -


     07. Using Seaborn for Graphs.mp4 -


     07. Using Seaborn for Graphs.vtt -


     08. How to Interpret the Regression Table.mp4 -


     08. How to Interpret the Regression Table.vtt -


     09. Decomposition of Variability.mp4 -


     09. Decomposition of Variability.vtt -


     10. What is the OLS.mp4 -


     10. What is the OLS.vtt -


     11. R-Squared.mp4 -


     11. R-Squared.vtt -


     01. Course-notes-regression-analysis.pdf -


     05. 1.01.Simple-linear-regression.csv -


     05. Simple-linear-regression-with-comments.ipynb -


     05. Simple-linear-regression.ipynb -


     06. real-estate-price-size.csv -


     06. Simple-Linear-Regression-Exercise-Solution.ipynb -


     06. Simple-Linear-Regression-Exercise.ipynb -


     01. Multiple Linear Regression.mp4 -


     01. Multiple Linear Regression.vtt -


     02. Adjusted R-Squared.mp4 -


     02. Adjusted R-Squared.vtt -


     03. Multiple Linear Regression Exercise.html -


     04. Test for Significance of the Model (F-Test).mp4 -


     04. Test for Significance of the Model (F-Test).vtt -


     05. OLS Assumptions.mp4 -


     05. OLS Assumptions.vtt -


     06. A1 Linearity.mp4 -


     06. A1 Linearity.vtt -


     07. A2 No Endogeneity.mp4 -


     07. A2 No Endogeneity.vtt -


     08. A3 Normality and Homoscedasticity.mp4 -


     08. A3 Normality and Homoscedasticity.vtt -


     09. A4 No Autocorrelation.mp4 -


     09. A4 No Autocorrelation.vtt -


     10. A5 No Multicollinearity.mp4 -


     10. A5 No Multicollinearity.vtt -


     11. Dealing with Categorical Data - Dummy Variables.mp4 -


     11. Dealing with Categorical Data - Dummy Variables.vtt -


     12. Dealing with Categorical Data - Dummy Variables.html -


     13. Making Predictions with the Linear Regression.mp4 -


     13. Making Predictions with the Linear Regression.vtt -


     02. 1.02.Multiple-linear-regression.csv -


     02. Multiple-linear-regression-and-Adjusted-R-squared-with-comments.ipynb -


     02. Multiple-linear-regression-and-Adjusted-R-squared.ipynb -


     03. Multiple-Linear-Regression-Exercise-Solution.ipynb -


     03. Multiple-Linear-Regression-Exercise.ipynb -


     03. real-estate-price-size-year.csv -


     11. 1.03.Dummies.csv -


     11. Dummy-variables-with-comments.ipynb -


     11. Dummy-Variables.ipynb -


     12. Multiple-Linear-Regression-with-Dummies-Exercise-Solution.ipynb -


     12. Multiple-Linear-Regression-with-Dummies-Exercise.ipynb -


     12. real-estate-price-size-year-view.csv -


     13. Making-predictions-with-comments.ipynb -


     13. Making-predictions.ipynb -


     01. What is sklearn and How is it Different from Other Packages.mp4 -


     01. What is sklearn and How is it Different from Other Packages.vtt -


     02. How are we Going to Approach this Section.mp4 -


     02. How are we Going to Approach this Section.vtt -


     03. Simple Linear Regression with sklearn.mp4 -


     03. Simple Linear Regression with sklearn.vtt -


     04. Simple Linear Regression with sklearn - A StatsModels-like Summary Table.mp4 -


     04. Simple Linear Regression with sklearn - A StatsModels-like Summary Table.vtt -


     05. A Note on Normalization.html -


     06. Simple Linear Regression with sklearn - Exercise.html -


     07. Multiple Linear Regression with sklearn.mp4 -


     07. Multiple Linear Regression with sklearn.vtt -


     08. Calculating the Adjusted R-Squared in sklearn.mp4 -


     08. Calculating the Adjusted R-Squared in sklearn.vtt -


     09. Calculating the Adjusted R-Squared in sklearn - Exercise.html -


     10. Feature Selection (F-regression).mp4 -


     10. Feature Selection (F-regression).vtt -


     11. A Note on Calculation of P-values with sklearn.html -


     12. Creating a Summary Table with P-values.mp4 -


     12. Creating a Summary Table with P-values.vtt -


     13. Multiple Linear Regression - Exercise.html -


     14. Feature Scaling (Standardization).mp4 -


     14. Feature Scaling (Standardization).vtt -


     15. Feature Selection through Standardization of Weights.mp4 -


     15. Feature Selection through Standardization of Weights.vtt -


     16. Predicting with the Standardized Coefficients.mp4 -


     16. Predicting with the Standardized Coefficients.vtt -


     17. Feature Scaling (Standardization) - Exercise.html -


     18. Underfitting and Overfitting.mp4 -


     18. Underfitting and Overfitting.vtt -


     19. Train - Test Split Explained.mp4 -


     19. Train - Test Split Explained.vtt -


     03. 1.01.Simple-linear-regression.csv -


     03. sklearn-Simple-Linear-Regression-with-comments.ipynb -


     03. sklearn-Simple-Linear-Regression.ipynb -


     04. 1.01.Simple-linear-regression.csv -


     04. sklearn-Simple-Linear-Regression-with-comments.ipynb -


     04. sklearn-Simple-Linear-Regression.ipynb -


     06. real-estate-price-size.csv -


     06. Simple-Linear-Regression-with-sklearn-Exercise-Solution.ipynb -


     06. Simple-Linear-Regression-with-sklearn-Exercise.ipynb -


     07. 1.02.Multiple-linear-regression.csv -


     07. sklearn-Multiple-Linear-Regression-with-comments.ipynb -


     07. sklearn-Multiple-Linear-Regression.ipynb -


     08. 1.02.Multiple-linear-regression.csv -


     08. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-with-comments.ipynb -


     08. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared.ipynb -


     09. 1.02.Multiple-linear-regression.csv -


     09. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise-Solution.ipynb -


     09. sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise.ipynb -


     10. 1.02.Multiple-linear-regression.csv -


     10. sklearn-Feature-Selection-with-F-regression-with-comments.ipynb -


     10. sklearn-Feature-Selection-with-F-regression.ipynb -


     11. 1.02.Multiple-linear-regression.csv -


     11. sklearn-How-to-properly-include-p-values.ipynb -


     12. 1.02.Multiple-linear-regression.csv -


     12. sklearn-Multiple-Linear-Regression-Summary-Table-with-comments.ipynb -


     12. sklearn-Multiple-Linear-Regression-Summary-Table.ipynb -


     13. real-estate-price-size-year.csv -


     13. sklearn-Multiple-Linear-Regression-Exercise-Solution.ipynb -


     13. sklearn-Multiple-Linear-Regression-Exercise.ipynb -


     14. 1.02.Multiple-linear-regression.csv -


     14. SKLEAR-1.IPY -


     14. sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-1.ipynb -


     15. 1.02.Multiple-linear-regression.csv -


     15. SKLEAR-1.IPY -


     15. sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-2.ipynb -


     16. 1.02.Multiple-linear-regression.csv -


     16. sklearn-Making-Predictions-with-the-Standardized-Coefficients-with-comments.ipynb -


     16. sklearn-Making-Predictions-with-the-Standardized-Coefficients.ipynb -


     17. real-estate-price-size-year.csv -


     17. sklearn-Feature-Scaling-Exercise-Solution.ipynb -


     17. sklearn-Feature-Scaling-Exercise.ipynb -


     19. sklearn-Train-Test-Split-with-comments.ipynb -


     19. sklearn-Train-Test-Split.ipynb -


     01. Practical Example Linear Regression (Part 1).mp4 -


     01. Practical Example Linear Regression (Part 1).vtt -


     02. Practical Example Linear Regression (Part 2).mp4 -


     02. Practical Example Linear Regression (Part 2).vtt -


     03. A Note on Multicollinearity.html -


     04. Practical Example Linear Regression (Part 3).mp4 -


     04. Practical Example Linear Regression (Part 3).vtt -


     05. Dummies and Variance Inflation Factor - Exercise.html -


     06. Practical Example Linear Regression (Part 4).mp4 -


     06. Practical Example Linear Regression (Part 4).vtt -


     07. Dummy Variables - Exercise.html -


     08. Practical Example Linear Regression (Part 5).mp4 -


     08. Practical Example Linear Regression (Part 5).vtt -


     09. Linear Regression - Exercise.html -


     01. 1.04.Real-life-example.csv -


     01. sklearn-Linear-Regression-Practical-Example-Part-1-with-comments.ipynb -


     01. sklearn-Linear-Regression-Practical-Example-Part-1.ipynb -


     02. 1.04.Real-life-example.csv -


     02. sklearn-Linear-Regression-Practical-Example-Part-2-with-comments.ipynb -


     02. sklearn-Linear-Regression-Practical-Example-Part-2.ipynb -


     04. sklearn-Linear-Regression-Practical-Example-Part-3-with-comments.ipynb -


     04. sklearn-Linear-Regression-Practical-Example-Part-3.ipynb -


     05. 1.04.Real-life-example.csv -


     05. sklearn-Dummies-and-VIF-Exercise-Solution.ipynb -


     05. sklearn-Dummies-and-VIF-Exercise.ipynb -


     06. 1.04.Real-life-example.csv -


     06. sklearn-Linear-Regression-Practical-Example-Part-4-with-comments.ipynb -


     06. sklearn-Linear-Regression-Practical-Example-Part-4.ipynb -


     08. 1.04.Real-life-example.csv -


     08. sklearn-Linear-Regression-Practical-Example-Part-5-with-comments.ipynb -


     08. sklearn-Linear-Regression-Practical-Example-Part-5.ipynb -


     01. Introduction to Logistic Regression.mp4 -


     01. Introduction to Logistic Regression.vtt -


     02. A Simple Example in Python.mp4 -


     02. A Simple Example in Python.vtt -


     03. Logistic vs Logit Function.mp4 -


     03. Logistic vs Logit Function.vtt -


     04. Building a Logistic Regression.mp4 -


     04. Building a Logistic Regression.vtt -


     05. Building a Logistic Regression - Exercise.html -


     06. An Invaluable Coding Tip.mp4 -


     06. An Invaluable Coding Tip.vtt -


     07. Understanding Logistic Regression Tables.mp4 -


     07. Understanding Logistic Regression Tables.vtt -


     08. Understanding Logistic Regression Tables - Exercise.html -


     09. What do the Odds Actually Mean.mp4 -


     09. What do the Odds Actually Mean.vtt -


     10. Binary Predictors in a Logistic Regression.mp4 -


     10. Binary Predictors in a Logistic Regression.vtt -


     11. Binary Predictors in a Logistic Regression - Exercise.html -


     12. Calculating the Accuracy of the Model.mp4 -


     12. Calculating the Accuracy of the Model.vtt -


     13. Calculating the Accuracy of the Model.html -


     14. Underfitting and Overfitting.mp4 -


     14. Underfitting and Overfitting.vtt -


     15. Testing the Model.mp4 -


     15. Testing the Model.vtt -


     16. Testing the Model - Exercise.html -


     01. Course-Notes-Logistic-Regression.pdf -


     02. 2.01.Admittance.csv -


     02. Admittance-with-comments.ipynb -


     02. Admittance.ipynb -


     02. Course-Notes-Logistic-Regression.pdf -


     04. Admittance-regression-summary-error.ipynb -


     04. Admittance-regression-tables-fixed-error.ipynb -


     04. Admittance-regression.ipynb -


     05. Building-a-Logistic-Regression-Exercise.ipynb -


     05. Building-a-Logistic-Regression-Solution.ipynb -


     05. Example-bank-data.csv -


     08. Bank-data.csv -


     08. Understanding-Logistic-Regression-Tables-Exercise.ipynb -


     08. Understanding-Logistic-Regression-Tables-Solution.ipynb -


     10. 2.02.Binary-predictors.csv -


     10. Binary-predictors.ipynb -


     11. Bank-data.csv -


     11. Binary-Predictors-in-a-Logistic-Regression-Exercise.ipynb -


     11. Binary-Predictors-in-a-Logistic-Regression-Solution.ipynb -


     12. Accuracy-with-comments.ipynb -


     12. Accuracy.ipynb -


     13. Bank-data.csv -


     13. Calculating-the-Accuracy-of-the-Model-Exercise.ipynb -


     13. Calculating-the-Accuracy-of-the-Model-Solution.ipynb -


     15. 2.03.Test-dataset.csv -


     15. Testing-the-model-with-comments.ipynb -


     15. Testing-the-model.ipynb -


     16. Bank-data-testing.csv -


     16. Bank-data.csv -


     16. Testing-the-Model-Exercise.ipynb -


     16. Testing-the-Model-Solution.ipynb -


     01. Introduction to Cluster Analysis.mp4 -


     01. Introduction to Cluster Analysis.vtt -


     02. Some Examples of Clusters.mp4 -


     02. Some Examples of Clusters.vtt -


     03. Difference between Classification and Clustering.mp4 -


     03. Difference between Classification and Clustering.vtt -


     04. Math Prerequisites.mp4 -


     04. Math Prerequisites.vtt -


     01. Course-Notes-Cluster-Analysis.pdf -


     02. Course-Notes-Cluster-Analysis.pdf -


     01. K-Means Clustering.mp4 -


     01. K-Means Clustering.vtt -


     02. A Simple Example of Clustering.mp4 -


     02. A Simple Example of Clustering.vtt -


     03. A Simple Example of Clustering - Exercise.html -


     04. Clustering Categorical Data.mp4 -


     04. Clustering Categorical Data.vtt -


     05. Clustering Categorical Data - Exercise.html -


     06. How to Choose the Number of Clusters.mp4 -


     06. How to Choose the Number of Clusters.vtt -


     07. How to Choose the Number of Clusters - Exercise.html -


     08. Pros and Cons of K-Means Clustering.mp4 -


     08. Pros and Cons of K-Means Clustering.vtt -


     09. To Standardize or not to Standardize.mp4 -


     09. To Standardize or not to Standardize.vtt -


     10. Relationship between Clustering and Regression.mp4 -


     10. Relationship between Clustering and Regression.vtt -


     11. Market Segmentation with Cluster Analysis (Part 1).mp4 -


     11. Market Segmentation with Cluster Analysis (Part 1).vtt -


     12. Market Segmentation with Cluster Analysis (Part 2).mp4 -


     12. Market Segmentation with Cluster Analysis (Part 2).vtt -


     13. How is Clustering Useful.mp4 -


     13. How is Clustering Useful.vtt -


     14. EXERCISE Species Segmentation with Cluster Analysis (Part 1).html -


     15. EXERCISE Species Segmentation with Cluster Analysis (Part 2).html -


     02. 3.01.Country-clusters.csv -


     02. Country-clusters-with-comments.ipynb -


     02. Country-clusters.ipynb -


     03. A-Simple-Example-of-Clustering-Exercise.ipynb -


     03. A-Simple-Example-of-Clustering-Solution.ipynb -


     03. Countries-exercise.csv -


     04. Categorical-data-with-comments.ipynb -


     04. Categorical-data.ipynb -


     05. Categorical.csv -


     05. Clustering-Categorical-Data-Exercise.ipynb -


     05. Clustering-Categorical-Data-Solution.ipynb -


     06. Selecting-the-number-of-clusters-with-comments.ipynb -


     06. Selecting-the-number-of-clusters.ipynb -


     07. Countries-exercise.csv -


     07. How-to-Choose-the-Number-of-Clusters-Exercise.ipynb -


     07. How-to-Choose-the-Number-of-Clusters-Solution.ipynb -


     11. 3.12.Example.csv -


     11. Market-segmentation-example-with-comments.ipynb -


     11. Market-segmentation-example.ipynb -


     12. Market-segmentation-example-Part2-with-comments.ipynb -


     12. Market-segmentation-example-Part2.ipynb -


     14. iris-dataset.csv -


     14. Species-Segmentation-with-Cluster-Analysis-Part-1-Exercise.ipynb -


     14. Species-Segmentation-with-Cluster-Analysis-Part-1-Solution.ipynb -


     15. iris-dataset.csv -


     15. iris-with-answers.csv -


     15. Species-Segmentation-with-Cluster-Analysis-Part-2-Exercise.ipynb -


     15. Species-Segmentation-with-Cluster-Analysis-Part-2-Solution.ipynb -


     01. Types of Clustering.mp4 -


     01. Types of Clustering.vtt -


     02. Dendrogram.mp4 -


     02. Dendrogram.vtt -


     03. Heatmaps.mp4 -


     03. Heatmaps.vtt -


     03. Country-clusters-standardized.csv -


     03. Heatmaps-with-comments.ipynb -


     03. Heatmaps.ipynb -


     01. Traditional data science methods and the role of ChatGPT.mp4 -


     01. Traditional data science methods and the role of ChatGPT.vtt -


     02. How to install ChatGPT.mp4 -


     02. How to install ChatGPT.vtt -


     03. How ChatGPT can boost your productivity.mp4 -


     03. How ChatGPT can boost your productivity.vtt -


     04. Data Preprocessing with ChatGPT.mp4 -


     04. Data Preprocessing with ChatGPT.vtt -


     05. First attempt at machine learning with ChatGPT.mp4 -


     05. First attempt at machine learning with ChatGPT.vtt -


     06. Analyzing a client database with ChatGPT in Python.mp4 -


     06. Analyzing a client database with ChatGPT in Python.vtt -


     07. Analyzing a client database with ChatGPT in Python – analyzing top products.mp4 -


     07. Analyzing a client database with ChatGPT in Python – analyzing top products.vtt -


     08. Analyzing a client database with ChatGPT in Python – analyzing top clients, RFM.mp4 -


     08. Analyzing a client database with ChatGPT in Python – analyzing top clients, RFM.vtt -


     09. Exploratory data analysis (EDA) with ChatGPT - histogram and scatter plot.mp4 -


     09. Exploratory data analysis (EDA) with ChatGPT - histogram and scatter plot.vtt -


     10. Exploratory data analysis (EDA) with ChatGPT - correlation matrix, outlier detec.mp4 -


     10. Exploratory data analysis (EDA) with ChatGPT - correlation matrix, outlier detec.vtt -


     11. Assignment 1.html -


     12. Hypothesis testing with ChatGPT.mp4 -


     12. Hypothesis testing with ChatGPT.vtt -


     13. Marvels comic book database Intro to Regular Expressions (RegEx).mp4 -


     13. Marvels comic book database Intro to Regular Expressions (RegEx).vtt -


     14. Decoding comic book data Python Regular Expressions and ChatGPT.mp4 -


     14. Decoding comic book data Python Regular Expressions and ChatGPT.vtt -


     15. Assignment 2.html -


     16. Algorithm recommendation Movie Database Analysis with ChatGPT.mp4 -


     16. Algorithm recommendation Movie Database Analysis with ChatGPT.vtt -


     17. Algorithm recommendation recommendation engine for movies with ChatGPT.mp4 -


     17. Algorithm recommendation recommendation engine for movies with ChatGPT.vtt -


     18. Ethical principles in data and AI utilization.mp4 -


     18. Ethical principles in data and AI utilization.vtt -


     19. Using ChatGPT for ethical considerations.mp4 -


     19. Using ChatGPT for ethical considerations.vtt -


     04. Data-Preprocessing-Medical-Data.ipynb -


     04. patients.csv -


     05. diagnosis-mapping.csv -


     05. Medical-Data-ML-Attempt.ipynb -


     05. patients-preprocessed.csv -


     06. customers.csv -


     06. orders.csv -


     06. products.csv -


     06. ratings.csv -


     08. Furniture-store-data-analysis.ipynb -


     10. Properties-analysis.ipynb -


     10. properties.csv -


     12. Students-Hypothesis-Testing.ipynb -


     12. students.csv -


     14. Marvel-Comics-Reg-Ex.ipynb -


     16. ratings-small.csv -


     17. Movies-Data-Base-Recommendation-Engine.ipynb -


     19. friendships.csv -


     19. interactions.csv -


     19. posts.csv -


     19. users.csv -


     Marvel_Comics.csv -


     movies_metadata.csv -


     01. Intro to the Case Study.mp4 -


     01. Intro to the Case Study.vtt -


     02. The Naive Bayes Algorithm.mp4 -


     02. The Naive Bayes Algorithm.vtt -


     03. Tokenization and Vectorization.mp4 -


     03. Tokenization and Vectorization.vtt -


     04. Imbalanced Data Sets.mp4 -


     04. Imbalanced Data Sets.vtt -


     05. Overcome Imbalanced Data in Machine Learning.mp4 -


     05. Overcome Imbalanced Data in Machine Learning.vtt -


     06. Loading the Dataset and Preprocessing.mp4 -


     06. Loading the Dataset and Preprocessing.vtt -


     07. Optimizing User Reviews Data Preprocessing & EDA.mp4 -


     07. Optimizing User Reviews Data Preprocessing & EDA.vtt -


     08. Reg Ex for Analyzing Text Review Data.mp4 -


     08. Reg Ex for Analyzing Text Review Data.vtt -


     09. Understanding Differences between Multinomial and Bernouilli Naive Bayes.mp4 -


     09. Understanding Differences between Multinomial and Bernouilli Naive Bayes.vtt -


     10. Machine Learning with Naïve Bayes (First Attempt).mp4 -


     10. Machine Learning with Naïve Bayes (First Attempt).vtt -


     11. Machine Learning with Naïve Bayes – converting the problem to a binary one.mp4 -


     11. Machine Learning with Naïve Bayes – converting the problem to a binary one.vtt -


     12. Testing the Model on New Data.mp4 -


     12. Testing the Model on New Data.vtt -


     12. 365-User-Reviews-Naive-Bayes-Sentiment-Analysis.ipynb -


     12. user-courses-review-test-set.csv -


     01. What is a Matrix.mp4 -


     01. What is a Matrix.vtt -


     02. Scalars and Vectors.mp4 -


     02. Scalars and Vectors.vtt -


     03. Linear Algebra and Geometry.mp4 -


     03. Linear Algebra and Geometry.vtt -


     04. Arrays in Python - A Convenient Way To Represent Matrices.mp4 -


     04. Arrays in Python - A Convenient Way To Represent Matrices.vtt -


     05. What is a Tensor.mp4 -


     05. What is a Tensor.vtt -


     06. Addition and Subtraction of Matrices.mp4 -


     06. Addition and Subtraction of Matrices.vtt -


     07. Errors when Adding Matrices.mp4 -


     07. Errors when Adding Matrices.vtt -


     08. Transpose of a Matrix.mp4 -


     08. Transpose of a Matrix.vtt -


     09. Dot Product.mp4 -


     09. Dot Product.vtt -


     10. Dot Product of Matrices.mp4 -


     10. Dot Product of Matrices.vtt -


     11. Why is Linear Algebra Useful.mp4 -


     11. Why is Linear Algebra Useful.vtt -


     04. Scalars-Vectors-and-Matrices.ipynb -


     05. Tensors.ipynb -


     06. Adding-and-subtracting-matrices.ipynb -


     07. Errors-when-adding-scalars-vectors-and-matrices-in-Python.ipynb -


     08. Tranpose-of-a-matrix.ipynb -


     09. Dot-product.ipynb -


     10. Dot-product-Part-2.ipynb -


     01. What to Expect from this Part.mp4 -


     01. What to Expect from this Part.vtt -


     01. Introduction to Neural Networks.mp4 -


     01. Introduction to Neural Networks.vtt -


     02. Training the Model.mp4 -


     02. Training the Model.vtt -


     03. Types of Machine Learning.mp4 -


     03. Types of Machine Learning.vtt -


     04. The Linear Model (Linear Algebraic Version).mp4 -


     04. The Linear Model (Linear Algebraic Version).vtt -


     05. The Linear Model with Multiple Inputs.mp4 -


     05. The Linear Model with Multiple Inputs.vtt -


     06. The Linear model with Multiple Inputs and Multiple Outputs.mp4 -


     06. The Linear model with Multiple Inputs and Multiple Outputs.vtt -


     07. Graphical Representation of Simple Neural Networks.mp4 -


     07. Graphical Representation of Simple Neural Networks.vtt -


     08. What is the Objective Function.mp4 -


     08. What is the Objective Function.vtt -


     09. Common Objective Functions L2-norm Loss.mp4 -


     09. Common Objective Functions L2-norm Loss.vtt -


     10. Common Objective Functions Cross-Entropy Loss.mp4 -


     10. Common Objective Functions Cross-Entropy Loss.vtt -


     11. Optimization Algorithm 1-Parameter Gradient Descent.mp4 -


     11. Optimization Algorithm 1-Parameter Gradient Descent.vtt -


     12. Optimization Algorithm n-Parameter Gradient Descent.mp4 -


     12. Optimization Algorithm n-Parameter Gradient Descent.vtt -


     01. Course-Notes-Section-2.pdf -


     02. Course-Notes-Section-2.pdf -


     11. GD-function-example.xlsx -


     01. Basic NN Example (Part 1).mp4 -


     01. Basic NN Example (Part 1).vtt -


     02. Basic NN Example (Part 2).mp4 -


     02. Basic NN Example (Part 2).vtt -


     03. Basic NN Example (Part 3).mp4 -


     03. Basic NN Example (Part 3).vtt -


     04. Basic NN Example (Part 4).mp4 -


     04. Basic NN Example (Part 4).vtt -


     05. Basic NN Example Exercises.html -


     01. Minimal-example-Part-1.ipynb -


     01. Shortcuts-for-Jupyter.pdf -


     02. Minimal-example-Part-2.ipynb -


     03. Minimal-example-Part-3.ipynb -


     04. Minimal-example-Part-4-Complete.ipynb -


     05. Minimal-example-All-Exercises.ipynb -


     05. Minimal-example-Exercise-1-Solution.ipynb -


     05. Minimal-example-Exercise-2-Solution.ipynb -


     05. Minimal-example-Exercise-3.a.Solution.ipynb -


     05. Minimal-example-Exercise-3.b.Solution.ipynb -


     05. Minimal-example-Exercise-3.c.Solution.ipynb -


     05. Minimal-example-Exercise-3.d.Solution.ipynb -


     05. Minimal-example-Exercise-4-Solution.ipynb -


     05. Minimal-example-Exercise-5-Solution.ipynb -


     05. Minimal-example-Exercise-6-Solution.ipynb -


     05. Minimal-example-Exercise-6.ipynb -


     01. How to Install TensorFlow 2.0.mp4 -


     01. How to Install TensorFlow 2.0.vtt -


     02. TensorFlow Outline and Comparison with Other Libraries.mp4 -


     02. TensorFlow Outline and Comparison with Other Libraries.vtt -


     03. TensorFlow 1 vs TensorFlow 2.mp4 -


     03. TensorFlow 1 vs TensorFlow 2.vtt -


     04. A Note on TensorFlow 2 Syntax.mp4 -


     04. A Note on TensorFlow 2 Syntax.vtt -


     05. Types of File Formats Supporting TensorFlow.mp4 -


     05. Types of File Formats Supporting TensorFlow.vtt -


     06. Outlining the Model with TensorFlow 2.mp4 -


     06. Outlining the Model with TensorFlow 2.vtt -


     07. Interpreting the Result and Extracting the Weights and Bias.mp4 -


     07. Interpreting the Result and Extracting the Weights and Bias.vtt -


     08. Customizing a TensorFlow 2 Model.mp4 -


     08. Customizing a TensorFlow 2 Model.vtt -


     09. Basic NN with TensorFlow Exercises.html -


     01. Shortcuts-for-Jupyter.pdf -


     05. TensorFlow-Minimal-example-Part1.ipynb -


     06. TensorFlow-Minimal-example-Part2.ipynb -


     07. TensorFlow-Minimal-example-Part3.ipynb -


     08. TensorFlow-Minimal-example-complete-with-comments.ipynb -


     08. TensorFlow-Minimal-example-complete.ipynb -


     09. TensorFlow-Minimal-example-All-exercises.ipynb -


     09. TensorFlow-Minimal-example-Exercise-1-Solution.ipynb -


     09. TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb -


     09. TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb -


     09. TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb -


     01. What is a Layer.mp4 -


     01. What is a Layer.vtt -


     02. What is a Deep Net.mp4 -


     02. What is a Deep Net.vtt -


     03. Digging into a Deep Net.mp4 -


     03. Digging into a Deep Net.vtt -


     04. Non-Linearities and their Purpose.mp4 -


     04. Non-Linearities and their Purpose.vtt -


     05. Activation Functions.mp4 -


     05. Activation Functions.vtt -


     06. Activation Functions Softmax Activation.mp4 -


     06. Activation Functions Softmax Activation.vtt -


     07. Backpropagation.mp4 -


     07. Backpropagation.vtt -


     08. Backpropagation Picture.mp4 -


     08. Backpropagation Picture.vtt -


     09. Backpropagation - A Peek into the Mathematics of Optimization.html -


     01. Course-Notes-Section-6.pdf -


     02. Course-Notes-Section-6.pdf -


     09. Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf -


     01. What is Overfitting.mp4 -


     01. What is Overfitting.vtt -


     02. Underfitting and Overfitting for Classification.mp4 -


     02. Underfitting and Overfitting for Classification.vtt -


     03. What is Validation.mp4 -


     03. What is Validation.vtt -


     04. Training, Validation, and Test Datasets.mp4 -


     04. Training, Validation, and Test Datasets.vtt -


     05. N-Fold Cross Validation.mp4 -


     05. N-Fold Cross Validation.vtt -


     06. Early Stopping or When to Stop Training.mp4 -


     06. Early Stopping or When to Stop Training.vtt -


     01. What is Initialization.mp4 -


     01. What is Initialization.vtt -


     02. Types of Simple Initializations.mp4 -


     02. Types of Simple Initializations.vtt -


     03. State-of-the-Art Method - (Xavier) Glorot Initialization.mp4 -


     03. State-of-the-Art Method - (Xavier) Glorot Initialization.vtt -


     01. Stochastic Gradient Descent.mp4 -


     01. Stochastic Gradient Descent.vtt -


     02. Problems with Gradient Descent.mp4 -


     02. Problems with Gradient Descent.vtt -


     03. Momentum.mp4 -


     03. Momentum.vtt -


     04. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.mp4 -


     04. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.vtt -


     05. Learning Rate Schedules Visualized.mp4 -


     05. Learning Rate Schedules Visualized.vtt -


     06. Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).mp4 -


     06. Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).vtt -


     07. Adam (Adaptive Moment Estimation).mp4 -


     07. Adam (Adaptive Moment Estimation).vtt -


     01. Preprocessing Introduction.mp4 -


     01. Preprocessing Introduction.vtt -


     02. Types of Basic Preprocessing.mp4 -


     02. Types of Basic Preprocessing.vtt -


     03. Standardization.mp4 -


     03. Standardization.vtt -


     04. Preprocessing Categorical Data.mp4 -


     04. Preprocessing Categorical Data.vtt -


     05. Binary and One-Hot Encoding.mp4 -


     05. Binary and One-Hot Encoding.vtt -


     01. MNIST The Dataset.mp4 -


     01. MNIST The Dataset.vtt -


     02. MNIST How to Tackle the MNIST.mp4 -


     02. MNIST How to Tackle the MNIST.vtt -


     03. MNIST Importing the Relevant Packages and Loading the Data.mp4 -


     03. MNIST Importing the Relevant Packages and Loading the Data.vtt -


     04. MNIST Preprocess the Data - Create a Validation Set and Scale It.mp4 -


     04. MNIST Preprocess the Data - Create a Validation Set and Scale It.vtt -


     05. MNIST Preprocess the Data - Scale the Test Data - Exercise.html -


     06. MNIST Preprocess the Data - Shuffle and Batch.mp4 -


     06. MNIST Preprocess the Data - Shuffle and Batch.vtt -


     07. MNIST Preprocess the Data - Shuffle and Batch - Exercise.html -


     08. MNIST Outline the Model.mp4 -


     08. MNIST Outline the Model.vtt -


     09. MNIST Select the Loss and the Optimizer.mp4 -


     09. MNIST Select the Loss and the Optimizer.vtt -


     10. MNIST Learning.mp4 -


     10. MNIST Learning.vtt -


     11. MNIST - Exercises.html -


     12. MNIST Testing the Model.mp4 -


     12. MNIST Testing the Model.vtt -


     03. TensorFlow-MNIST-Part1-with-comments.ipynb -


     05. TensorFlow-MNIST-Part2-with-comments.ipynb -


     07. TensorFlow-MNIST-Part3-with-comments.ipynb -


     08. TensorFlow-MNIST-Part4-with-comments.ipynb -


     09. TensorFlow-MNIST-Part5-with-comments.ipynb -


     10. TensorFlow-MNIST-Part6-with-comments.ipynb -


     11. 1.TensorFlow-MNIST-Width-Solution.ipynb -


     11. 2.TensorFlow-MNIST-Depth-Solution.ipynb -


     11. 3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb -


     11. 4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb -


     11. 5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb -


     11. 6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb -


     11. 7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb -


     11. 8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb -


     11. 9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb -


     11. TensorFlow-MNIST-All-Exercises.ipynb -


     11. TensorFlow-MNIST-around-98-percent-accuracy.ipynb -


     12. TensorFlow-MNIST-complete-with-comments.ipynb -


     12. TensorFlow-MNIST-complete.ipynb -


     01. Business Case Exploring the Dataset and Identifying Predictors.mp4 -


     01. Business Case Exploring the Dataset and Identifying Predictors.vtt -


     02. Business Case Outlining the Solution.mp4 -


     02. Business Case Outlining the Solution.vtt -


     03. Business Case Balancing the Dataset.mp4 -


     03. Business Case Balancing the Dataset.vtt -


     04. Business Case Preprocessing the Data.mp4 -


     04. Business Case Preprocessing the Data.vtt -


     05. Business Case Preprocessing the Data - Exercise.html -


     06. Business Case Load the Preprocessed Data.mp4 -


     06. Business Case Load the Preprocessed Data.vtt -


     07. Business Case Load the Preprocessed Data - Exercise.html -


     08. Business Case Learning and Interpreting the Result.mp4 -


     08. Business Case Learning and Interpreting the Result.vtt -


     09. Business Case Setting an Early Stopping Mechanism.mp4 -


     09. Business Case Setting an Early Stopping Mechanism.vtt -


     10. Setting an Early Stopping Mechanism - Exercise.html -


     11. Business Case Testing the Model.mp4 -


     11. Business Case Testing the Model.vtt -


     12. Business Case Final Exercise.html -


     01. Audiobooks-data.csv -


     04. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb -


     04. TensorFlow-Audiobooks-Preprocessing.ipynb -


     05. TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb -


     05. TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb -


     07. TensorFlow-Audiobooks-Machine-Learning-Part1-with-comments.ipynb -


     08. TensorFlow-Audiobooks-Machine-Learning-Part2-with-comments.ipynb -


     09. TensorFlow-Audiobooks-Machine-Learning-Part3-with-comments.ipynb -


     11. TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb -


     12. TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb -


     01. Summary on What You've Learned.mp4 -


     01. Summary on What You've Learned.vtt -


     02. What's Further out there in terms of Machine Learning.mp4 -


     02. What's Further out there in terms of Machine Learning.vtt -


     03. DeepMind and Deep Learning.html -


     04. An overview of CNNs.mp4 -


     04. An overview of CNNs.vtt -


     05. An Overview of RNNs.mp4 -


     05. An Overview of RNNs.vtt -


     06. An Overview of non-NN Approaches.mp4 -


     06. An Overview of non-NN Approaches.vtt -


     01. READ ME!!!!.html -


     02. How to Install TensorFlow 1.mp4 -


     02. How to Install TensorFlow 1.vtt -


     03. A Note on Installing Packages in Anaconda.html -


     04. TensorFlow Intro.mp4 -


     04. TensorFlow Intro.vtt -


     05. Actual Introduction to TensorFlow.mp4 -


     05. Actual Introduction to TensorFlow.vtt -


     06. Types of File Formats, supporting Tensors.mp4 -


     06. Types of File Formats, supporting Tensors.vtt -


     07. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.mp4 -


     07. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.vtt -


     08. Basic NN Example with TF Loss Function and Gradient Descent.mp4 -


     08. Basic NN Example with TF Loss Function and Gradient Descent.vtt -


     09. Basic NN Example with TF Model Output.mp4 -


     09. Basic NN Example with TF Model Output.vtt -


     10. Basic NN Example with TF Exercises.html -


     05. Shortcuts-for-Jupyter.pdf -


     06. 5.3.TensorFlow-Minimal-example-Part-1.ipynb -


     07. 5.4.TensorFlow-Minimal-example-Part-2.ipynb -


     08. 5.5.TensorFlow-Minimal-example-Part-3.ipynb -


     09. 5.6.TensorFlow-Minimal-example-complete.ipynb -


     10. TensorFlow-Minimal-Example-All-Exercises.ipynb -


     10. TensorFlow-Minimal-Example-Exercise-1-Solution.ipynb -


     10. TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb -


     10. TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb -


     10. TensorFlow-Minimal-Example-Exercise-2-3-Solution.ipynb -


     10. TensorFlow-Minimal-Example-Exercise-2-4-Solution.ipynb -


     10. TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb -


     10. TensorFlow-Minimal-Example-Exercise-4-Solution.ipynb -


     01. MNIST What is the MNIST Dataset.mp4 -


     01. MNIST What is the MNIST Dataset.vtt -


     02. MNIST How to Tackle the MNIST.mp4 -


     02. MNIST How to Tackle the MNIST.vtt -


     03. MNIST Relevant Packages.mp4 -


     03. MNIST Relevant Packages.vtt -


     04. MNIST Model Outline.mp4 -


     04. MNIST Model Outline.vtt -


     05. MNIST Loss and Optimization Algorithm.mp4 -


     05. MNIST Loss and Optimization Algorithm.vtt -


     06. Calculating the Accuracy of the Model.mp4 -


     06. Calculating the Accuracy of the Model.vtt -


     07. MNIST Batching and Early Stopping.mp4 -


     07. MNIST Batching and Early Stopping.vtt -


     08. MNIST Learning.mp4 -


     08. MNIST Learning.vtt -


     09. MNIST Results and Testing.mp4 -


     09. MNIST Results and Testing.vtt -


     10. MNIST Exercises.html -


     11. MNIST Solutions.html -


     03. 12.3.TensorFlow-MNIST-with-comments-Part-1.ipynb -


     04. 12.4.TensorFlow-MNIST-with-comments-Part-2.ipynb -


     05. 12.5.TensorFlow-MNIST-with-comments-Part-3.ipynb -


     06. 12.6.TensorFlow-MNIST-with-comments-Part-4.ipynb -


     07. 12.7.TensorFlow-MNIST-with-comments-Part-5.ipynb -


     08. 12.8.TensorFlow-MNIST-with-comments-Part-6.ipynb -


     09. 12.9.TensorFlow-MNIST-with-comments.ipynb -


     10. TensorFlow-MNIST-Exercises-All.ipynb -


     11. 0.TensorFlow-MNIST-take-note-of-time-Solution.ipynb -


     11. 1.TensorFlow-MNIST-Width-Solution.ipynb -


     11. 2.TensorFlow-MNIST-Depth-Solution.ipynb -


     11. 3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb -


     11. 4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb -


     11. 5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb -


     11. 6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb -


     11. 7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb -


     11. 8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb -


     11. 9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb -


     11. TensorFlow-MNIST-around-98-percent-accuracy.ipynb -


     01. Business Case Getting Acquainted with the Dataset.mp4 -


     01. Business Case Getting Acquainted with the Dataset.vtt -


     02. Business Case Outlining the Solution.mp4 -


     02. Business Case Outlining the Solution.vtt -


     03. The Importance of Working with a Balanced Dataset.mp4 -


     03. The Importance of Working with a Balanced Dataset.vtt -


     04. Business Case Preprocessing.mp4 -


     04. Business Case Preprocessing.vtt -


     05. Business Case Preprocessing Exercise.html -


     06. Creating a Data Provider.mp4 -


     06. Creating a Data Provider.vtt -


     07. Business Case Model Outline.mp4 -


     07. Business Case Model Outline.vtt -


     08. Business Case Optimization.mp4 -


     08. Business Case Optimization.vtt -


     09. Business Case Interpretation.mp4 -


     09. Business Case Interpretation.vtt -


     10. Business Case Testing the Model.mp4 -


     10. Business Case Testing the Model.vtt -


     11. Business Case A Comment on the Homework.mp4 -


     11. Business Case A Comment on the Homework.vtt -


     12. Business Case Final Exercise.html -


     01. Audiobooks-data.csv -


     03. Audiobooks-data.csv -


     04. Audiobooks-data.csv -


     04. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb -


     04. TensorFlow-Audiobooks-Preprocessing.ipynb -


     05. Audiobooks-data.csv -


     05. TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb -


     05. TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb -


     07. TensorFlow-Audiobooks-Outlining-the-model-with-comments.ipynb -


     07. TensorFlow-Audiobooks-Outlining-the-model.ipynb -


     08. TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb -


     08. TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb -


     09. TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb -


     09. TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb -


     11. Audiobooks-data.csv -


     11. TensorFlow-Audiobooks-Machine-learning-Homework.ipynb -


     11. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb -


     12. Audiobooks-data.csv -


     12. TensorFlow-Audiobooks-Machine-learning-Homework.ipynb -


     12. TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb -


     01. What are Data, Servers, Clients, Requests, and Responses.mp4 -


     01. What are Data, Servers, Clients, Requests, and Responses.vtt -


     02. What are Data Connectivity, APIs, and Endpoints.mp4 -


     02. What are Data Connectivity, APIs, and Endpoints.vtt -


     03. Taking a Closer Look at APIs.mp4 -


     03. Taking a Closer Look at APIs.vtt -


     04. Communication between Software Products through Text Files.mp4 -


     04. Communication between Software Products through Text Files.vtt -


     05. Software Integration - Explained.mp4 -


     05. Software Integration - Explained.vtt -


     01. Game Plan for this Python, SQL, and Tableau Business Exercise.mp4 -


     01. Game Plan for this Python, SQL, and Tableau Business Exercise.vtt -


     02. The Business Task.mp4 -


     02. The Business Task.vtt -


     03. Introducing the Data Set.mp4 -


     03. Introducing the Data Set.vtt -


     01. What to Expect from the Following Sections.html -


     02. Importing the Absenteeism Data in Python.mp4 -


     02. Importing the Absenteeism Data in Python.vtt -


     03. Checking the Content of the Data Set.mp4 -


     03. Checking the Content of the Data Set.vtt -


     04. Introduction to Terms with Multiple Meanings.mp4 -


     04. Introduction to Terms with Multiple Meanings.vtt -


     05. What's Regression Analysis - a Quick Refresher.html -


     06. Using a Statistical Approach towards the Solution to the Exercise.mp4 -


     06. Using a Statistical Approach towards the Solution to the Exercise.vtt -


     07. Dropping a Column from a DataFrame in Python.mp4 -


     07. Dropping a Column from a DataFrame in Python.vtt -


     08. EXERCISE - Dropping a Column from a DataFrame in Python.html -


     09. SOLUTION - Dropping a Column from a DataFrame in Python.html -


     10. Analyzing the Reasons for Absence.mp4 -


     10. Analyzing the Reasons for Absence.vtt -


     11. Obtaining Dummies from a Single Feature.mp4 -


     11. Obtaining Dummies from a Single Feature.vtt -


     12. EXERCISE - Obtaining Dummies from a Single Feature.html -


     13. SOLUTION - Obtaining Dummies from a Single Feature.html -


     14. Dropping a Dummy Variable from the Data Set.html -


     15. More on Dummy Variables A Statistical Perspective.mp4 -


     15. More on Dummy Variables A Statistical Perspective.vtt -


     16. Classifying the Various Reasons for Absence.mp4 -


     16. Classifying the Various Reasons for Absence.vtt -


     17. Using .concat() in Python.mp4 -


     17. Using .concat() in Python.vtt -


     18. EXERCISE - Using .concat() in Python.html -


     19. SOLUTION - Using .concat() in Python.html -


     20. Reordering Columns in a Pandas DataFrame in Python.mp4 -


     20. Reordering Columns in a Pandas DataFrame in Python.vtt -


     21. EXERCISE - Reordering Columns in a Pandas DataFrame in Python.html -


     22. SOLUTION - Reordering Columns in a Pandas DataFrame in Python.html -


     23. Creating Checkpoints while Coding in Jupyter.mp4 -


     23. Creating Checkpoints while Coding in Jupyter.vtt -


     24. EXERCISE - Creating Checkpoints while Coding in Jupyter.html -


     25. SOLUTION - Creating Checkpoints while Coding in Jupyter.html -


     26. Analyzing the Dates from the Initial Data Set.mp4 -


     26. Analyzing the Dates from the Initial Data Set.vtt -


     27. Extracting the Month Value from the Date Column.mp4 -


     27. Extracting the Month Value from the Date Column.vtt -


     28. Extracting the Day of the Week from the Date Column.mp4 -


     28. Extracting the Day of the Week from the Date Column.vtt -


     29. EXERCISE - Removing the Date Column.html -


     30. Analyzing Several Straightforward Columns for this Exercise.mp4 -


     30. Analyzing Several Straightforward Columns for this Exercise.vtt -


     31. Working on Education, Children, and Pets.mp4 -


     31. Working on Education, Children, and Pets.vtt -


     32. Final Remarks of this Section.mp4 -


     32. Final Remarks of this Section.vtt -


     33. A Note on Exporting Your Data as a .csv File.html -


     01. Absenteeism-data.csv -


     01. data-preprocessing-homework.pdf -


     01. df-preprocessed.csv -


     23. Absenteeism-Exercise-Preprocessing-df-reason-mod.ipynb -


     29. Absenteeism-Exercise-Preprocessing-ChP-df-date-reason-mod.ipynb -


     29. Absenteeism-Exercise-Preprocessing-LECTURES.ipynb -


     29. Absenteeism-Exercise-Removing-the-Date-Column-SOLUTION.ipynb -


     32. Absenteeism-Exercise-EXERCISES-and-SOLUTIONS.ipynb -


     32. Absenteeism-Exercise-Preprocessing-df-preprocessed.ipynb -


     01. Exploring the Problem with a Machine Learning Mindset.mp4 -


     01. Exploring the Problem with a Machine Learning Mindset.vtt -


     02. Creating the Targets for the Logistic Regression.mp4 -


     02. Creating the Targets for the Logistic Regression.vtt -


     03. Selecting the Inputs for the Logistic Regression.mp4 -


     03. Selecting the Inputs for the Logistic Regression.vtt -


     04. Standardizing the Data.mp4 -


     04. Standardizing the Data.vtt -


     05. Splitting the Data for Training and Testing.mp4 -


     05. Splitting the Data for Training and Testing.vtt -


     06. Fitting the Model and Assessing its Accuracy.mp4 -


     06. Fitting the Model and Assessing its Accuracy.vtt -


     07. Creating a Summary Table with the Coefficients and Intercept.mp4 -


     07. Creating a Summary Table with the Coefficients and Intercept.vtt -


     08. Interpreting the Coefficients for Our Problem.mp4 -


     08. Interpreting the Coefficients for Our Problem.vtt -


     09. Standardizing only the Numerical Variables (Creating a Custom Scaler).mp4 -


     09. Standardizing only the Numerical Variables (Creating a Custom Scaler).vtt -


     10. Interpreting the Coefficients of the Logistic Regression.mp4 -


     10. Interpreting the Coefficients of the Logistic Regression.vtt -


     11. Backward Elimination or How to Simplify Your Model.mp4 -


     11. Backward Elimination or How to Simplify Your Model.vtt -


     12. Testing the Model We Created.mp4 -


     12. Testing the Model We Created.vtt -


     13. Saving the Model and Preparing it for Deployment.mp4 -


     13. Saving the Model and Preparing it for Deployment.vtt -


     14. ARTICLE - A Note on 'pickling'.html -


     15. EXERCISE - Saving the Model (and Scaler).html -


     16. Preparing the Deployment of the Model through a Module.mp4 -


     16. Preparing the Deployment of the Model through a Module.vtt -


     01. Absenteeism-preprocessed.csv -


     01. Are You Sure You're All Set.html -


     02. Deploying the 'absenteeism_module' - Part I.mp4 -


     02. Deploying the 'absenteeism_module' - Part I.vtt -


     03. Deploying the 'absenteeism_module' - Part II.mp4 -


     03. Deploying the 'absenteeism_module' - Part II.vtt -


     04. Exporting the Obtained Data Set as a .csv.html -


     01. Absenteeism-Exercise-Integration.ipynb -


     01. absenteeism-module.py -


     01. Absenteeism-new-data.csv -


     01. model -


     01. scaler -


     04. Absenteeism-Exercise-Deploying-the-absenteeism-module.ipynb -


     01. EXERCISE - Age vs Probability.html -


     02. Analyzing Age vs Probability in Tableau.mp4 -


     02. Analyzing Age vs Probability in Tableau.vtt -


     03. EXERCISE - Reasons vs Probability.html -


     04. Analyzing Reasons vs Probability in Tableau.mp4 -


     04. Analyzing Reasons vs Probability in Tableau.vtt -


     05. EXERCISE - Transportation Expense vs Probability.html -


     06. Analyzing Transportation Expense vs Probability in Tableau.mp4 -


     06. Analyzing Transportation Expense vs Probability in Tableau.vtt -


     01. Absenteeism-predictions.csv -


     02. Absenteeism-predictions.csv -


     01. Using the .format() Method.mp4 -


     01. Using the .format() Method.vtt -


     02. Iterating Over Range Objects.mp4 -


     02. Iterating Over Range Objects.vtt -


     03. Introduction to Nested For Loops.mp4 -


     03. Introduction to Nested For Loops.vtt -


     04. Triple Nested For Loops.mp4 -


     04. Triple Nested For Loops.vtt -


     05. List Comprehensions.mp4 -


     05. List Comprehensions.vtt -


     06. Anonymous (Lambda) Functions.mp4 -


     06. Anonymous (Lambda) Functions.vtt -


     01. Additional-Python-Tools-Exercises.ipynb -


     01. Additional-Python-Tools-Lectures.ipynb -


     01. Additional-Python-Tools-Solutions.ipynb -


     06. Additional-Python-Tools-Exercises.ipynb -


     06. Additional-Python-Tools-Lectures.ipynb -


     06. Additional-Python-Tools-Solutions.ipynb -


     01. Introduction to pandas Series.mp4 -


     01. Introduction to pandas Series.vtt -


     02. A Note on Completing the Upcoming Coding Exercises.html -


     03. Working with Methods in Python - Part I.mp4 -


     03. Working with Methods in Python - Part I.vtt -


     04. Working with Methods in Python - Part II.mp4 -


     04. Working with Methods in Python - Part II.vtt -


     05. Parameters and Arguments in pandas.mp4 -


     05. Parameters and Arguments in pandas.vtt -


     06. Using .unique() and .nunique().mp4 -


     06. Using .unique() and .nunique().vtt -


     07. Using .sort_values().mp4 -


     07. Using .sort_values().vtt -


     08. Introduction to pandas DataFrames - Part I.mp4 -


     08. Introduction to pandas DataFrames - Part I.vtt -


     09. Introduction to pandas DataFrames - Part II.mp4 -


     09. Introduction to pandas DataFrames - Part II.vtt -


     10. pandas DataFrames - Common Attributes.mp4 -


     10. pandas DataFrames - Common Attributes.vtt -


     11. Data Selection in pandas DataFrames.mp4 -


     11. Data Selection in pandas DataFrames.vtt -


     12. pandas DataFrames - Indexing with .iloc[].mp4 -


     12. pandas DataFrames - Indexing with .iloc[].vtt -


     13. pandas DataFrames - Indexing with .loc[].mp4 -


     13. pandas DataFrames - Indexing with .loc[].vtt -


     01. Lending-company.csv -


     01. Location.csv -


     01. pandas-Fundamentals-Exercises.ipynb -


     01. pandas-Fundamentals-Lectures.ipynb -


     01. pandas-Fundamentals-Solutions.ipynb -


     01. Region.csv -


     01. Sales-products.csv -


     13. Lending-company.csv -


     13. Location.csv -


     13. pandas-Fundamentals-Exercises.ipynb -


     13. pandas-Fundamentals-Lectures.ipynb -


     13. pandas-Fundamentals-Solutions.ipynb -


     13. Region.csv -


     13. Sales-products.csv -


     01. Bonus Lecture Next Steps.html -


     01. 365-Data-Science-Data-Science-Interview-Questions-Guide.pdf -

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