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1. Welcome to the course!/6.1 Machine_Learning_A-Z_New.zip.zip 239.5 MB
36. Kernel PCA/3. Kernel PCA in R.mp4 59.3 MB
1. Welcome to the course!/7. Updates on Udemy Reviews.mp4 55.5 MB
39. XGBoost/5. THANK YOU bonus video.mp4 54.8 MB
12. Logistic Regression/13. Logistic Regression in R - Step 5.mp4 54.2 MB
35. Linear Discriminant Analysis (LDA)/4. LDA in R.mp4 53.8 MB
17. Decision Tree Classification/4. Decision Tree Classification in R.mp4 53.7 MB
18. Random Forest Classification/4. Random Forest Classification in R.mp4 51.8 MB
31. Artificial Neural Networks/13. ANN in Python - Step 2.mp4 50.4 MB
39. XGBoost/4. XGBoost in R.mp4 49.6 MB
27. Upper Confidence Bound (UCB)/10. Upper Confidence Bound in R - Step 3.mp4 49.5 MB
18. Random Forest Classification/3. Random Forest Classification in Python.mp4 49.5 MB
32. Convolutional Neural Networks/20. CNN in Python - Step 9.mp4 49.1 MB
7. Support Vector Regression (SVR)/2. SVR Intuition.mp4 48.9 MB
7. Support Vector Regression (SVR)/3. SVR in Python.mp4 48.4 MB
35. Linear Discriminant Analysis (LDA)/3. LDA in Python.mp4 47.6 MB
8. Decision Tree Regression/4. Decision Tree Regression in R.mp4 46.5 MB
16. Naive Bayes/1. Bayes Theorem.mp4 46.0 MB
24. Apriori/5. Apriori in R - Step 3.mp4 46.0 MB
38. Model Selection/3. k-Fold Cross Validation in R.mp4 45.8 MB