Udemy - Machine Learning in Bioinformatics - From Theory to Pract...

Files:

• Get Bonus Downloads Here.url (0.2 KB)
~Get Your Files Here ! 1 - Introduction
• 1 -Introduction to Machine Learning.mp4 (87.9 MB)
• 2 -Setting up Environment for ML workflowsCode.mp4 (63.8 MB)
10 - Final Projects
• 1 -Capstone Projects.mp4 (42.6 MB)
• 1 -Capstone Projects.pptx (95.3 KB)
2 - Preparing Biological Data for Machine Learning
• 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)
3 - Supervised Machine Learning
• 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 (0.2 KB)
• 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 (0.5 KB)
4 - Unsupervised Learning
• 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 (0.3 KB)
• 6 -single cell using scanpy.single-cell-using-scanpy (1.1 MB)
5 - Advance Machine Learning
• 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 (0.2 KB)
6 - Practical Application of ML
• 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 (0.8 KB)
• 2 -protein_sequences.fasta (0.8 KB)
• 2 -protein_tree.newick (0.1 KB)
• 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 (0.2 KB)
• 4 -ML in Metagenomics.mp4 (31.0 MB)
• 4 -file.py (2.4 KB)
• 5 -Summary of ML Applications.mp4 (10.0 MB)
7 - Evaluating and Optimizing Machine Learning Models
• 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)
8 - Data Integration and Multi-Omics in Machine Learning
• 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)
9 - Ethical and Practical Considerations in Machine Learning for Bioinformatics
• 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 (0.1 KB)