[GigaCourse.com] Udemy - Deep Learning with Keras and Tensorflow in Python and R

1. 15. R - Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 221.28 MB
2. 12. Python - Regression problems and Functional API/1. Building Neural Network for Regression Problem.mp4 159.61 MB
3. 14. Python - Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 155.27 MB
4. 13. R - Regression Problem and Functional API/1. Building Regression Model with Functional AP.mp4 134.28 MB
5. 11. R - Building and training the Model/1. Building,Compiling and Training.mp4 133.87 MB
6. 5. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 125.13 MB
7. 9. Dataset for classification problem/3. R - Dataset, Normalization and Test-Train set.mp4 114.50 MB
8. 18. Add on Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.mp4 102.88 MB
9. 11. R - Building and training the Model/2. Evaluating and Predicting.mp4 101.64 MB
10. 18. Add on Data Preprocessing/8. EDD in R.mp4 99.31 MB
11. 3. Setting up R Studio and R Crash Course/7. Creating Barplots in R.mp4 99.08 MB
12. 12. Python - Regression problems and Functional API/2. Using Functional API for complex architectures.mp4 94.35 MB
13. 4. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.mp4 88.67 MB
14. 3. Setting up R Studio and R Crash Course/3. Packages in R.mp4 84.94 MB
15. 10. Python - Building and training the Model/3. Compiling and Training the Neural Network model.mp4 83.62 MB
16. 13. R - Regression Problem and Functional API/2. Complex Architectures using Functional API.mp4 81.49 MB
17. 10. Python - Building and training the Model/2. Building the Neural Network using Keras.mp4 81.04 MB
18. 19. Test Train Split/4. Test train split in R.mp4 77.43 MB
19. 18. Add on Data Preprocessing/10. Outlier Treatment in Python.mp4 71.93 MB
20. 10. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.mp4 71.54 MB
21. 18. Add on Data Preprocessing/3. The Data and the Data Dictionary.mp4 71.01 MB
22. 2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4 66.76 MB
23. 2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4 65.99 MB
24. 6. Important concepts Common Interview questions/1. Some Important Concepts.mp4 63.67 MB
25. 18. Add on Data Preprocessing/7. EDD in Python.mp4 63.26 MB
26. 16. Python - Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 62.10 MB
27. 17. R - Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 62.09 MB
28. 5. Neural Networks - Stacking cells to create network/2. Gradient Descent.mp4 61.79 MB
29. 2. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp4 61.76 MB
30. 3. Setting up R Studio and R Crash Course/6. Inputting data part 3 Importing from CSV or Text files.mp4 61.51 MB
31. 9. Dataset for classification problem/1. Python - Dataset for classification problem.mp4 57.52 MB
32. 18. Add on Data Preprocessing/18. Variable transformation in R.mp4 56.76 MB
33. 2. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.mp4 48.01 MB
34. 7. Standard Model Parameters/1. Hyperparameters.mp4 46.44 MB
35. 19. Test Train Split/3. Test train split in Python.mp4 45.95 MB
36. 4. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.mp4 45.83 MB
37. 9. Dataset for classification problem/2. Python - Normalization and Test-Train split.mp4 45.27 MB
38. 18. Add on Data Preprocessing/17. Variable transformation and deletion in Python.mp4 45.18 MB
39. 18. Add on Data Preprocessing/22. Dummy variable creation in R.mp4 45.03 MB
40. 2. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.mp4 44.94 MB
41. 3. Setting up R Studio and R Crash Course/8. Creating Histograms in R.mp4 43.02 MB
42. 19. Test Train Split/1. Test-train split.mp4 42.87 MB
43. 2. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.mp4 41.90 MB
44. 3. Setting up R Studio and R Crash Course/4. Inputting data part 1 Inbuilt datasets of R.mp4 41.70 MB
45. 5. Neural Networks - Stacking cells to create network/1. Basic Terminologies.mp4 41.40 MB
46. 2. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.mp4 41.32 MB
47. 3. Setting up R Studio and R Crash Course/2. Basics of R and R studio.mp4 39.79 MB
48. 18. Add on Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp4 37.72 MB
49. 3. Setting up R Studio and R Crash Course/1. Installing R and R studio.mp4 36.55 MB
50. 4. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.mp4 35.46 MB