Python for Data Science and Machine Learning 2024 CourseWikia
Seeders : 28 Leechers : 12
| Torrent Hash : | A9D21C30345795FF7D99F04ED9BEED0526DB4A90 |
| Torrent Added : | at Sept. 11, 2024, 5:44 p.m. in Other |
| Torrent Size : | 3.1 GB |
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Python for Data Science and Machine Learning 2024 CourseWikia
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Python for Data Science and Machine Learning 2024 CourseWikia
Get Bonus Downloads Here.url -
1 - Setting up the Environment.mp4 -
2 - Introduction to Python Tools.mp4 -
10 - Strings 1.mp4 -
11 - Strings 2.mp4 -
12 - 7-Dictionaries-Sets.ipynb -
12 - Dictionaries.mp4 -
13 - Sets.mp4 -
3 - 1.Arithmetic.ipynb -
3 - Arithmetic Operations in Python.mp4 -
4 - 2.Data-Types.ipynb -
4 - Data Types.mp4 -
5 - 4.Variables.ipynb -
5 - Variables.mp4 -
6 - 5.Lists.ipynb -
6 - Intro to Lists.mp4 -
7 - Lists 2.mp4 -
8 - Lists 3.mp4 -
9 - 6.Tuples-and-strings.ipynb -
9 - Tuples.mp4 -
14 - 1.Pandas-Intro.ipynb -
14 - Introduction to Pandas.mp4 -
15 - 2.Pandas-Series-Part-1.ipynb -
15 - Pandas Series Part 1.mp4 -
16 - 3.Pandas-Series-Part-2.ipynb -
16 - Pandas Series Part 2.mp4 -
17 - 4.Pandas-Series-Unique.ipynb -
17 - Pandas Series Unique.mp4 -
18 - 5.Sorting-a-Series.ipynb -
18 - Pandas Series Sorting.mp4 -
19 - 6.Dataframes-Intro.ipynb -
19 - Introduction to DataFrames.mp4 -
20 - 7-Data-from-csv-file.ipynb -
20 - Accessing csv files.mp4 -
20 - titanic.csv -
21 - 8.Data-Inspection.ipynb -
21 - Data Inspection.mp4 -
22 - 9.Dataframes-Index.ipynb -
22 - Dataframe Indexing 1.mp4 -
23 - 11.Indexing-in-Dataframes.ipynb -
23 - Dataframe Indexing 2.mp4 -
24 - 10.Dataframe-Filter.ipynb -
24 - Dataframe Filter.mp4 -
25 - 12.Position-based-Index-iloc.ipynb -
25 - IPL.csv -
25 - Position based indexing using iloc.mp4 -
26 - 13.Index-based-Slicing-iloc.ipynb -
26 - Dataframe Slicing using iloc.mp4 -
26 - IPL.csv -
27 - 14.Label-based-Slicing-using-loc.ipynb -
27 - IPL.csv -
27 - Label based Slicing using loc.mp4 -
28 - 15.loc-with-numeric-index.ipynb -
28 - Loc with numeric index.mp4 -
29 - 16.Reset-index.ipynb -
29 - IPL.csv -
29 - Reset Index.mp4 -
30 - 17.Rename-columns.ipynb -
30 - Rename Columns.mp4 -
30 - data.csv -
31 - 18.Conditional-Filter.ipynb -
31 - Conditional Filter.mp4 -
31 - titanic.csv -
32 - 19.Advanced-Filter-Dataframe.ipynb -
32 - Advanced Filter.mp4 -
32 - titanic.csv -
33 - 20.Handling-Missing-Values-Part-1.ipynb -
33 - Missing Values Part 1.mp4 -
33 - missing.csv -
34 - 21.Handling-Missing-Values-Part-2.ipynb -
34 - Missing Values Part 2.mp4 -
34 - titanic.csv -
35 - 22.Groupby.ipynb -
35 - Group by.mp4 -
36 - 23.Introduction-to-Time-Series-Data.ipynb -
36 - Intro to Time Series.mp4 -
36 - minute.csv -
37 - 27-Downloading-Data-yfinance-API.ipynb -
37 - Downloading Data yfinance API.mp4 -
38 - 24.Convert-string-to-datetime-column.ipynb -
38 - String to Datetime.mp4 -
38 - minute.csv -
39 - 10.Accessing-Data.ipynb -
39 - Reading Files.mp4 -
39 - minute.csv -
40 - 11-Accessing-MySQL-Database.ipynb -
40 - Working with My Sql Database.mp4 -
41 - 25.Slice-Time-Series-Data.ipynb -
41 - Slice Time Series Data.mp4 -
41 - minute.csv -
42 - 28.Pivot.ipynb -
42 - Pivot DataFrame.mp4 -
42 - bank-data.csv -
43 - 26.Resample.ipynb -
43 - Resample DataFrame.mp4 -
43 - tick.csv -
44 - 29.Data-Normalization.ipynb -
44 - Data Normalization.mp4 -
44 - bank-data.csv -
45 - 21-Frequency-Tables.ipynb -
45 - Frequency Tables.mp4 -
45 - titanic.csv -
46 - 22-Pandas.ipynb -
46 - Visualization Part 1 Pandas.mp4 -
46 - diamond.csv -
47 - Charts-with-Matplotlibs.ipynb -
47 - Visualization Part 2 Matplotlib.mp4 -
47 - minute.csv -
48 - 30.Calculate-Price-Changes.ipynb -
48 - Calculate Price Changes.mp4 -
48 - daily.csv -
49 - 31.Calculate-Financial-Returns.ipynb -
49 - Calculate Financial Returns.mp4 -
49 - daily.csv -
50 - 33.TVPI-or-multiples.ipynb -
50 - TVPI.mp4 -
50 - daily.csv -
51 - 34.CAGR-vs-Annual-Returns.ipynb -
51 - CAGR.mp4 -
52 - 35.Geometric-Returns.ipynb -
52 - Geometric Returns.mp4 -
53 - 32.Risk-vs-Reward.ipynb -
53 - Risk vs Returns.mp4 -
53 - daily.csv -
54 - 36.Simple-vs-Compound-Interest.ipynb -
54 - Simple vs Compound Interest.mp4 -
55 - 37-Continuous-Compounding.ipynb -
55 - Continuous Compounding.mp4 -
56 - 38.Intro-to-Log-Returns.ipynb -
56 - Intro to log Returns.mp4 -
57 - 39.Daily-Returns-vs-Log-Returns.ipynb -
57 - Daily Return vs Log Returns.mp4 -
58 - 40.More-about-Log-Returns.ipynb -
58 - More About Log Returns.mp4 -
59 - 25.Intro-to-Statistics.ipynb -
59 - Descriptive Statistics.mp4 -
59 - marks.csv -
60 - Five Point Summary.mp4 -
60 - Five-point-Summary.ipynb -
61 - Moving Averages.mp4 -
61 - Moving-Averages.ipynb -
61 - nifty.csv -
62 - 27.Confidence-Intervals.ipynb -
62 - Confidence Intervals.mp4 -
63 - 26.Distributions.ipynb -
63 - Statistical Distributions.mp4 -
64 - 28.Hypothesis.ipynb -
64 - Hypothesis Testing.mp4 -
65 - 29-Analysis-of-variance.ipynb -
65 - Analysis of Variance.mp4 -
66 - 30-Linear-Regression.ipynb -
66 - Linear Regression.mp4 -
66 - mtcars.csv -
67 - 31-Logistic-Regression.ipynb -
67 - Logistic Regression.mp4 -
67 - titanic.csv -
68 - 32-Decision-Trees.ipynb -
68 - Decision Trees.mp4 -
69 - 33-Random-Forests.ipynb -
69 - Random Forests.mp4 -
Bonus Resources.txt -
Please login or create a FREE account to post comments
Get Bonus Downloads Here.url -
181 bytes
1 - Setting up the Environment.mp4 -
91.5 MB
2 - Introduction to Python Tools.mp4 -
153.5 MB
10 - Strings 1.mp4 -
28.9 MB
11 - Strings 2.mp4 -
28.8 MB
12 - 7-Dictionaries-Sets.ipynb -
9.0 KB
12 - Dictionaries.mp4 -
25.3 MB
13 - Sets.mp4 -
107.3 MB
3 - 1.Arithmetic.ipynb -
8.6 KB
3 - Arithmetic Operations in Python.mp4 -
33.3 MB
4 - 2.Data-Types.ipynb -
6.4 KB
4 - Data Types.mp4 -
31.2 MB
5 - 4.Variables.ipynb -
3.1 KB
5 - Variables.mp4 -
30.7 MB
6 - 5.Lists.ipynb -
11.2 KB
6 - Intro to Lists.mp4 -
22.6 MB
7 - Lists 2.mp4 -
40.8 MB
8 - Lists 3.mp4 -
39.8 MB
9 - 6.Tuples-and-strings.ipynb -
8.6 KB
9 - Tuples.mp4 -
30.9 MB
14 - 1.Pandas-Intro.ipynb -
1.5 KB
14 - Introduction to Pandas.mp4 -
135.0 MB
15 - 2.Pandas-Series-Part-1.ipynb -
5.2 KB
15 - Pandas Series Part 1.mp4 -
19.6 MB
16 - 3.Pandas-Series-Part-2.ipynb -
3.6 KB
16 - Pandas Series Part 2.mp4 -
28.4 MB
17 - 4.Pandas-Series-Unique.ipynb -
3.6 KB
17 - Pandas Series Unique.mp4 -
24.2 MB
18 - 5.Sorting-a-Series.ipynb -
6.3 KB
18 - Pandas Series Sorting.mp4 -
19.7 MB
19 - 6.Dataframes-Intro.ipynb -
4.5 KB
19 - Introduction to DataFrames.mp4 -
19.7 MB
20 - 7-Data-from-csv-file.ipynb -
2.4 KB
20 - Accessing csv files.mp4 -
73.0 MB
20 - titanic.csv -
58.9 KB
21 - 8.Data-Inspection.ipynb -
3.7 KB
21 - Data Inspection.mp4 -
54.8 MB
22 - 9.Dataframes-Index.ipynb -
3.3 KB
22 - Dataframe Indexing 1.mp4 -
38.4 MB
23 - 11.Indexing-in-Dataframes.ipynb -
2.6 KB
23 - Dataframe Indexing 2.mp4 -
17.6 MB
24 - 10.Dataframe-Filter.ipynb -
2.9 KB
24 - Dataframe Filter.mp4 -
25.4 MB
25 - 12.Position-based-Index-iloc.ipynb -
4.0 KB
25 - IPL.csv -
37.3 KB
25 - Position based indexing using iloc.mp4 -
84.8 MB
26 - 13.Index-based-Slicing-iloc.ipynb -
3.4 KB
26 - Dataframe Slicing using iloc.mp4 -
22.9 MB
26 - IPL.csv -
37.3 KB
27 - 14.Label-based-Slicing-using-loc.ipynb -
92.9 KB
27 - IPL.csv -
37.3 KB
27 - Label based Slicing using loc.mp4 -
39.9 MB
28 - 15.loc-with-numeric-index.ipynb -
2.5 KB
28 - Loc with numeric index.mp4 -
14.4 MB
29 - 16.Reset-index.ipynb -
3.3 KB
29 - IPL.csv -
37.3 KB
29 - Reset Index.mp4 -
35.5 MB
30 - 17.Rename-columns.ipynb -
5.4 KB
30 - Rename Columns.mp4 -
16.8 MB
30 - data.csv -
16 bytes
31 - 18.Conditional-Filter.ipynb -
3.8 KB
31 - Conditional Filter.mp4 -
41.1 MB
31 - titanic.csv -
58.9 KB
32 - 19.Advanced-Filter-Dataframe.ipynb -
2.6 KB
32 - Advanced Filter.mp4 -
18.4 MB
32 - titanic.csv -
58.9 KB
33 - 20.Handling-Missing-Values-Part-1.ipynb -
2.1 KB
33 - Missing Values Part 1.mp4 -
10.2 MB
33 - missing.csv -
54 bytes
34 - 21.Handling-Missing-Values-Part-2.ipynb -
4.9 KB
34 - Missing Values Part 2.mp4 -
54.1 MB
34 - titanic.csv -
58.9 KB
35 - 22.Groupby.ipynb -
5.8 KB
35 - Group by.mp4 -
32.7 MB
36 - 23.Introduction-to-Time-Series-Data.ipynb -
1.3 KB
36 - Intro to Time Series.mp4 -
23.0 MB
36 - minute.csv -
16.9 KB
37 - 27-Downloading-Data-yfinance-API.ipynb -
2.8 KB
37 - Downloading Data yfinance API.mp4 -
62.3 MB
38 - 24.Convert-string-to-datetime-column.ipynb -
4.4 KB
38 - String to Datetime.mp4 -
36.5 MB
38 - minute.csv -
16.9 KB
39 - 10.Accessing-Data.ipynb -
25.9 KB
39 - Reading Files.mp4 -
88.0 MB
39 - minute.csv -
16.9 KB
40 - 11-Accessing-MySQL-Database.ipynb -
5.1 KB
40 - Working with My Sql Database.mp4 -
57.0 MB
41 - 25.Slice-Time-Series-Data.ipynb -
2.4 KB
41 - Slice Time Series Data.mp4 -
12.1 MB
41 - minute.csv -
16.9 KB
42 - 28.Pivot.ipynb -
2.2 KB
42 - Pivot DataFrame.mp4 -
19.5 MB
42 - bank-data.csv -
244.3 KB
43 - 26.Resample.ipynb -
3.5 KB
43 - Resample DataFrame.mp4 -
33.3 MB
43 - tick.csv -
598.1 KB
44 - 29.Data-Normalization.ipynb -
2.2 KB
44 - Data Normalization.mp4 -
52.4 MB
44 - bank-data.csv -
244.3 KB
45 - 21-Frequency-Tables.ipynb -
37.4 KB
45 - Frequency Tables.mp4 -
84.6 MB
45 - titanic.csv -
58.9 KB
46 - 22-Pandas.ipynb -
311.5 KB
46 - Visualization Part 1 Pandas.mp4 -
91.7 MB
46 - diamond.csv -
4.0 KB
47 - Charts-with-Matplotlibs.ipynb -
9.9 KB
47 - Visualization Part 2 Matplotlib.mp4 -
64.0 MB
47 - minute.csv -
16.9 KB
48 - 30.Calculate-Price-Changes.ipynb -
2.1 KB
48 - Calculate Price Changes.mp4 -
14.6 MB
48 - daily.csv -
98.8 KB
49 - 31.Calculate-Financial-Returns.ipynb -
2.1 KB
49 - Calculate Financial Returns.mp4 -
8.0 MB
49 - daily.csv -
98.8 KB
50 - 33.TVPI-or-multiples.ipynb -
46.4 KB
50 - TVPI.mp4 -
33.1 MB
50 - daily.csv -
98.8 KB
51 - 34.CAGR-vs-Annual-Returns.ipynb -
64.6 KB
51 - CAGR.mp4 -
27.1 MB
52 - 35.Geometric-Returns.ipynb -
92.7 KB
52 - Geometric Returns.mp4 -
24.7 MB
53 - 32.Risk-vs-Reward.ipynb -
2.3 KB
53 - Risk vs Returns.mp4 -
17.3 MB
53 - daily.csv -
98.8 KB
54 - 36.Simple-vs-Compound-Interest.ipynb -
5.8 KB
54 - Simple vs Compound Interest.mp4 -
22.8 MB
55 - 37-Continuous-Compounding.ipynb -
5.1 KB
55 - Continuous Compounding.mp4 -
24.2 MB
56 - 38.Intro-to-Log-Returns.ipynb -
2.3 KB
56 - Intro to log Returns.mp4 -
19.1 MB
57 - 39.Daily-Returns-vs-Log-Returns.ipynb -
47.9 KB
57 - Daily Return vs Log Returns.mp4 -
46.4 MB
58 - 40.More-about-Log-Returns.ipynb -
148.8 KB
58 - More About Log Returns.mp4 -
45.2 MB
59 - 25.Intro-to-Statistics.ipynb -
231.5 KB
59 - Descriptive Statistics.mp4 -
108.4 MB
59 - marks.csv -
226 bytes
60 - Five Point Summary.mp4 -
34.1 MB
60 - Five-point-Summary.ipynb -
15.2 KB
61 - Moving Averages.mp4 -
89.3 MB
61 - Moving-Averages.ipynb -
240.3 KB
61 - nifty.csv -
98.8 KB
62 - 27.Confidence-Intervals.ipynb -
69.2 KB
62 - Confidence Intervals.mp4 -
77.0 MB
63 - 26.Distributions.ipynb -
135.3 KB
63 - Statistical Distributions.mp4 -
83.9 MB
64 - 28.Hypothesis.ipynb -
42.6 KB
64 - Hypothesis Testing.mp4 -
87.5 MB
65 - 29-Analysis-of-variance.ipynb -
21.5 KB
65 - Analysis of Variance.mp4 -
40.0 MB
66 - 30-Linear-Regression.ipynb -
150.5 KB
66 - Linear Regression.mp4 -
78.1 MB
66 - mtcars.csv -
1.7 KB
67 - 31-Logistic-Regression.ipynb -
30.7 KB
67 - Logistic Regression.mp4 -
56.8 MB
67 - titanic.csv -
58.9 KB
68 - 32-Decision-Trees.ipynb -
175.3 KB
68 - Decision Trees.mp4 -
83.6 MB
69 - 33-Random-Forests.ipynb -
5.8 KB
69 - Random Forests.mp4 -
39.0 MB
Bonus Resources.txt -
386 bytes
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