[FreeCourseSite.com] Udemy - Machine Learning & Deep Learning in Python & R

1. 27. ANN in R/8. Saving - Restoring Models and Using Callbacks.mp4 221.22 MB
2. 37. Time Series - Preprocessing in Python/3. Time Series - Visualization in Python.mp4 169.15 MB
3. 18. Ensemble technique 3 - Boosting/7. XGBoosting in R.mp4 165.18 MB
4. 26. ANN in Python/9. Building Neural Network for Regression Problem.mp4 159.64 MB
5. 26. ANN in Python/11. Saving - Restoring Models and Using Callbacks.mp4 155.21 MB
6. 23. Creating Support Vector Machine Model in R/3. Classification SVM model using Linear Kernel.mp4 142.50 MB
7. 27. ANN in R/6. Building Regression Model with Functional API.mp4 134.28 MB
8. 27. ANN in R/3. Building,Compiling and Training.mp4 133.86 MB
9. 34. Transfer Learning Basics/6. Project - Transfer Learning - VGG16.mp4 132.18 MB
10. 7. Linear Regression/20. Ridge regression and Lasso in Python.mp4 131.94 MB
11. 25. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 125.13 MB
12. 38. Time Series - Important Concepts/5. Differencing in Python.mp4 115.71 MB
13. 37. Time Series - Preprocessing in Python/5. Time Series - Feature Engineering in Python.mp4 115.40 MB
14. 27. ANN in R/2. Data Normalization and Test-Train Split.mp4 114.47 MB
15. 5. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4 111.79 MB
16. 37. Time Series - Preprocessing in Python/1. Data Loading in Python.mp4 111.47 MB
17. 23. Creating Support Vector Machine Model in R/7. SVM based Regression Model in R.mp4 108.67 MB
18. 7. Linear Regression/21. Ridge regression and Lasso in R.mp4 105.91 MB
19. 14. Simple Decision Trees/13. Building a Regression Tree in R.mp4 105.81 MB
20. 35. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).mp4 104.01 MB
21. 37. Time Series - Preprocessing in Python/7. Time Series - Upsampling and Downsampling in Python.mp4 103.09 MB
22. 6. Data Preprocessing/16. Bi-variate analysis and Variable transformation.mp4 102.80 MB
23. 27. ANN in R/4. Evaluating and Predicting.mp4 101.66 MB
24. 6. Data Preprocessing/8. EDD in R.mp4 99.32 MB
25. 3. Setting up R Studio and R crash course/7. Creating Barplots in R.mp4 99.05 MB
26. 7. Linear Regression/3. Assessing accuracy of predicted coefficients.mp4 94.32 MB
27. 26. ANN in Python/10. Using Functional API for complex architectures.mp4 94.31 MB
28. 18. Ensemble technique 3 - Boosting/5. AdaBoosting in R.mp4 90.80 MB
29. 32. Project Creating CNN model from scratch/1. Project in R - Data Preprocessing.mp4 89.87 MB
30. 24. Introduction - Deep Learning/4. Python - Creating Perceptron model.mp4 88.64 MB
31. 15. Simple Classification Tree/5. Building a classification Tree in R.mp4 87.14 MB
32. 27. ANN in R/5. ANN with NeuralNets Package.mp4 86.44 MB
33. 6. Data Preprocessing/25. Correlation Matrix in R.mp4 85.14 MB
34. 23. Creating Support Vector Machine Model in R/5. Polynomial Kernel with Hyperparameter Tuning.mp4 85.14 MB
35. 3. Setting up R Studio and R crash course/3. Packages in R.mp4 84.92 MB
36. 15. Simple Classification Tree/4. Classification tree in Python Training.mp4 84.71 MB
37. 14. Simple Decision Trees/18. Pruning a Tree in R.mp4 84.06 MB
38. 26. ANN in Python/7. Compiling and Training the Neural Network model.mp4 83.59 MB
39. 17. Ensemble technique 2 - Random Forests/3. Using Grid Search in Python.mp4 82.60 MB
40. 27. ANN in R/7. Complex Architectures using Functional API.mp4 81.48 MB
41. 26. ANN in Python/6. Building the Neural Network using Keras.mp4 81.02 MB
42. 7. Linear Regression/17. Subset selection techniques.mp4 80.96 MB
43. 8. Classification Models Data Preparation/1. The Data and the Data Dictionary.mp4 80.90 MB
44. 8. Classification Models Data Preparation/4. EDD in Python.mp4 79.48 MB
45. 16. Ensemble technique 1 - Bagging/2. Ensemble technique 1 - Bagging in Python.mp4 79.16 MB
46. 7. Linear Regression/15. Test-Train Split in R.mp4 77.42 MB
47. 12. K-Nearest Neighbors classifier/4. K-Nearest Neighbors classifier.mp4 77.23 MB
48. 18. Ensemble technique 3 - Boosting/6. Ensemble technique 3c - XGBoost in Python.mp4 76.80 MB
49. 40. Time Series - ARIMA model/3. ARIMA model in Python.mp4 76.22 MB
50. 11. Linear Discriminant Analysis (LDA)/3. Linear Discriminant Analysis in R.mp4 76.13 MB