Udemy Machine Learning in Bioinformatics From Theory to Pract
Seeders : 5 Leechers : 3
| Torrent Hash : | 5B5FFD02FD4C27E5052A2EE48C96537CAEAE0FF3 |
| Torrent Added : | at May 1, 2025, 8:21 a.m. in Other |
| Torrent Size : | 2.3 GB |
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Udemy Machine Learning in Bioinformatics From Theory to Pract
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Udemy Machine Learning in Bioinformatics From Theory to Pract
Get Bonus Downloads Here.url -
1 -Introduction to Machine Learning.mp4 -
2 -Setting up Environment for ML workflowsCode.mp4 -
1 -Capstone Projects.mp4 -
1 -Capstone Projects.pptx -
1 -Data cleaning, preprocessing, and feature engineering.mp4 -
2 -Data Preprocessing Techniques.mp4 -
2 -DataPreprocessing.ipynb -
3 -03_DataVisualization.ipynb -
3 -Data visualizations using python.mp4 -
1 -Introduction to Supervised Machine Learning.mp4 -
10 -Case Study PPI network models.mp4 -
10 -PPI Network.py -
10 -networks.csv -
2 -04_SimpleLinearRegression.ipynb -
2 -Simple Linear Regression.mp4 -
2 -headbrain.csv -
3 -09_Logistic_Regression.ipynb -
3 -Logistic Regression.mp4 -
3 -titanic.csv -
4 -10_K_Nearest_Neighbors.ipynb -
4 -KNN Classifier.mp4 -
4 -credit_data.csv -
5 -11_SupportVectorMachine.ipynb -
5 -SVM.mp4 -
6 -12_Naive_Bayes.ipynb -
6 -Naive bayes classifier.mp4 -
6 -credit_data.csv -
7 -13_Decision_Tree_Classifier.ipynb -
7 -Decision trees.mp4 -
7 -pima-indians-diabetes.csv -
8 -14_Random_Forest_Classification.ipynb -
8 -Random Forest Classifier.mp4 -
8 -mushrooms.csv -
9 -Case Study Cancer Classifier.mp4 -
9 -cancer-classsifier.py -
9 -expression_file.csv -
1 -Introduction to unsupervised learning.mp4 -
2 -Dimensionality Reduction in Bioinformatics.mp4 -
2 -Dimensionality Reduction in Bioinformatics.py -
3 -15_K_Means_Clustering.ipynb -
3 -K-means Clustering.mp4 -
3 -Quotes.csv -
4 -16_DBSCAN_Clustering.ipynb -
4 -DBSCAN.mp4 -
5 -17_Hierarchical_Clustering.ipynb -
5 -Hierarchical Clustering.mp4 -
6 -Case Study Single Cell analysis.mp4 -
6 -immune-cells.csv -
6 -single cell using scanpy.single-cell-using-scanpy -
1 -Introduction and explanation of advance machine learning models.mp4 -
2 -Case Study predicting DNA mutations using RNN.mp4 -
2 -Predicting-Dna-mutations-using-RNN.py -
2 -data.csv -
1 -Genomics Practical Application of ML.mp4 -
1 -V-C Model.py -
2 -ML in Proteomics.mp4 -
2 -aligned_sequences.fasta -
2 -protein_sequences.fasta -
2 -protein_tree.newick -
2 -proteomics.py -
3 -ML in Drug discovery.mp4 -
3 -QSAR-model.py -
3 -drug_target_data.csv -
4 -ML in Metagenomics.mp4 -
4 -file.py -
5 -Summary of ML Applications.mp4 -
1 -Evaluation and Optimization of Machine Learning Models in Bioinformatics.mp4 -
2 -Case Study Breast Cancer Prediction with poor and enhanced recall.mp4 -
2 -case-study.py -
1 -Data Integration and Multi-Omics in Machine Learning for Bioinformatics.mp4 -
2 -Case Study Multi-Omics in Cancer Research.mp4 -
2 -multi-omics-model.py -
1 -Bias and Fairness in ML Models and Case study of Polygenic Risk Scores.mp4 -
1 -PRS-model.py -
2 -Challenges in ML and Case Study of AI in COVID-19 Drug Discovery.mp4 -
2 -Drug-discovery-model.py -
Bonus Resources.txt -
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Get Bonus Downloads Here.url -
183 bytes
1 -Introduction to Machine Learning.mp4 -
87.9 MB
2 -Setting up Environment for ML workflowsCode.mp4 -
63.8 MB
1 -Capstone Projects.mp4 -
42.6 MB
1 -Capstone Projects.pptx -
95.3 KB
1 -Data cleaning, preprocessing, and feature engineering.mp4 -
73.3 MB
2 -Data Preprocessing Techniques.mp4 -
167.1 MB
2 -DataPreprocessing.ipynb -
621.4 KB
3 -03_DataVisualization.ipynb -
278.3 KB
3 -Data visualizations using python.mp4 -
136.2 MB
1 -Introduction to Supervised Machine Learning.mp4 -
81.3 MB
10 -Case Study PPI network models.mp4 -
64.9 MB
10 -PPI Network.py -
4.4 KB
10 -networks.csv -
155 bytes
2 -04_SimpleLinearRegression.ipynb -
54.7 KB
2 -Simple Linear Regression.mp4 -
84.4 MB
2 -headbrain.csv -
3.5 KB
3 -09_Logistic_Regression.ipynb -
32.5 KB
3 -Logistic Regression.mp4 -
52.7 MB
3 -titanic.csv -
105.7 KB
4 -10_K_Nearest_Neighbors.ipynb -
39.8 KB
4 -KNN Classifier.mp4 -
44.5 MB
4 -credit_data.csv -
149.5 KB
5 -11_SupportVectorMachine.ipynb -
27.1 KB
5 -SVM.mp4 -
45.0 MB
6 -12_Naive_Bayes.ipynb -
18.4 KB
6 -Naive bayes classifier.mp4 -
28.1 MB
6 -credit_data.csv -
149.5 KB
7 -13_Decision_Tree_Classifier.ipynb -
1.9 MB
7 -Decision trees.mp4 -
46.0 MB
7 -pima-indians-diabetes.csv -
23.5 KB
8 -14_Random_Forest_Classification.ipynb -
843.3 KB
8 -Random Forest Classifier.mp4 -
101.0 MB
8 -mushrooms.csv -
373.2 KB
9 -Case Study Cancer Classifier.mp4 -
54.4 MB
9 -cancer-classsifier.py -
2.5 KB
9 -expression_file.csv -
487 bytes
1 -Introduction to unsupervised learning.mp4 -
106.7 MB
2 -Dimensionality Reduction in Bioinformatics.mp4 -
44.9 MB
2 -Dimensionality Reduction in Bioinformatics.py -
1.3 KB
3 -15_K_Means_Clustering.ipynb -
19.1 KB
3 -K-means Clustering.mp4 -
60.3 MB
3 -Quotes.csv -
1.8 KB
4 -16_DBSCAN_Clustering.ipynb -
103.1 KB
4 -DBSCAN.mp4 -
55.5 MB
5 -17_Hierarchical_Clustering.ipynb -
26.4 KB
5 -Hierarchical Clustering.mp4 -
46.8 MB
6 -Case Study Single Cell analysis.mp4 -
118.9 MB
6 -immune-cells.csv -
338 bytes
6 -single cell using scanpy.single-cell-using-scanpy -
1.1 MB
1 -Introduction and explanation of advance machine learning models.mp4 -
52.0 MB
2 -Case Study predicting DNA mutations using RNN.mp4 -
55.1 MB
2 -Predicting-Dna-mutations-using-RNN.py -
3.0 KB
2 -data.csv -
249 bytes
1 -Genomics Practical Application of ML.mp4 -
54.7 MB
1 -V-C Model.py -
1.4 KB
2 -ML in Proteomics.mp4 -
74.9 MB
2 -aligned_sequences.fasta -
841 bytes
2 -protein_sequences.fasta -
839 bytes
2 -protein_tree.newick -
70 bytes
2 -proteomics.py -
5.5 KB
3 -ML in Drug discovery.mp4 -
53.6 MB
3 -QSAR-model.py -
5.8 KB
3 -drug_target_data.csv -
184 bytes
4 -ML in Metagenomics.mp4 -
31.0 MB
4 -file.py -
2.4 KB
5 -Summary of ML Applications.mp4 -
10.0 MB
1 -Evaluation and Optimization of Machine Learning Models in Bioinformatics.mp4 -
49.0 MB
2 -Case Study Breast Cancer Prediction with poor and enhanced recall.mp4 -
48.0 MB
2 -case-study.py -
4.8 KB
1 -Data Integration and Multi-Omics in Machine Learning for Bioinformatics.mp4 -
65.4 MB
2 -Case Study Multi-Omics in Cancer Research.mp4 -
47.8 MB
2 -multi-omics-model.py -
2.8 KB
1 -Bias and Fairness in ML Models and Case study of Polygenic Risk Scores.mp4 -
86.8 MB
1 -PRS-model.py -
4.1 KB
2 -Challenges in ML and Case Study of AI in COVID-19 Drug Discovery.mp4 -
64.3 MB
2 -Drug-discovery-model.py -
2.1 KB
Bonus Resources.txt -
70 bytes
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