Udemy - Master Deep Learning with TensorFlow in Python [DC]

Files:

• 1. Meet your instructors and why you should study machine learning.mp4 (105.8 MB)
• 1. Meet your instructors and why you should study machine learning.vtt (8.8 KB)
• 2. What does the course cover.mp4 (16.4 MB)
• 2. What does the course cover.vtt (5.5 KB)
• 3. What does the course cover - Quiz.html (0.2 KB)

• 1. Stochastic gradient descent.mp4 (9.4 MB)
• 1. Stochastic gradient descent.vtt (4.2 KB)
• 2. Gradient descent pitfalls.mp4 (4.3 MB)
• 2. Gradient descent pitfalls.vtt (2.5 KB)
• 3. Momentum.mp4 (6.1 MB)
• 3. Momentum.vtt (3.1 KB)
• 4. Learning rate schedules.mp4 (10.3 MB)
• 4. Learning rate schedules.vtt (5.3 KB)
• 5. Learning rate schedules. A picture.mp4 (3.1 MB)
• 5. Learning rate schedules. A picture.vtt (1.9 KB)
• 6. Adaptive learning rate schedules.mp4 (8.9 MB)
• 6. Adaptive learning rate schedules.vtt (4.6 KB)
• 7. Adaptive moment estimation.mp4 (7.8 MB)
• 7. Adaptive moment estimation.vtt (2.9 KB)

• 1. Preprocessing introduction.mp4 (8.4 MB)
• 1. Preprocessing introduction.vtt (3.4 KB)
• 2. Basic preprocessing.mp4 (3.7 MB)
• 2. Basic preprocessing.vtt (1.5 KB)
• 3. Standardization.mp4 (8.3 MB)
• 3. Standardization.vtt (5.3 KB)
• 4. Dealing with categorical data.mp4 (6.1 MB)
• 4. Dealing with categorical data.vtt (2.4 KB)
• 5. One-hot and binary encoding.mp4 (6.2 MB)
• 5. One-hot and binary encoding.vtt (4.2 KB)

• 1. The dataset.mp4 (7.4 MB)
• 1. The dataset.vtt (3.1 KB)
• 10. MNIST - exercises.html (2.3 KB)
• 10.1 MNIST_Exercises_All.html (0.1 KB)
• 11. MNIST - solutions.html (2.2 KB)
• 11.1 MNIST_Depth_Solution.html (0.1 KB)
• 11.10 MNIST_Learning_rate_Part_1_Solution.html (0.2 KB)
• 11.11 TensorFlow_MNIST_Activation_functions_Part_1_Solution.html (0.2 KB)
• 11.2 MNIST_take_note_of_time_Solution.html (0.2 KB)
• 11.3 Width_and_Depth_Solution.html (0.2 KB)
• 11.4 MNIST_Learning_rate_Part_2_Solution.html (0.2 KB)
• 11.5 MNIST_around_98_percent_accuracy_solution.html (0.2 KB)
• 11.6 MNIST_Batch_size_Part_2_Solution.html (0.2 KB)
• 11.7 MNIST_Width_Solution.html (0.1 KB)
• 11.8 MNIST_Batch_size_Part_1_Solution.html (0.2 KB)
• 11.9 MNIST_Activation_functions_Part_2_Solution.html (0.2 KB)
• 2. How to tackle the MNIST.mp4 (7.3 MB)
• 2. How to tackle the MNIST.vtt (3.2 KB)
• 3. Importing the relevant packages.mp4 (5.5 MB)
• 3. Importing the relevant packages.vtt (1.9 KB)
• 3.1 TensorFlow_MNIST_with_comments_Part_1.html (0.2 KB)
• 4. Outlining the model.mp4 (18.4 MB)
• 4. Outlining the model.vtt (7.8 KB)
• 4.1 TensorFlow_MNIST_with_comments_Part_2.html (0.2 KB)
• 5. Declaring the loss and the optimization algorithm.mp4 (7.1 MB)
• 5. Declaring the loss and the optimization algorithm.vtt (3.1 KB)
• 5.1 TensorFlow_MNIST_with_comments_Part_3.html (0.2 KB)
• 6. Accuracy of prediction.mp4 (12.4 MB)
• 6. Accuracy of prediction.vtt (4.6 KB)
• 6.1 TensorFlow_MNIST_with_comments_Part_4.html (0.2 KB)
• 7. Batching and early stopping.mp4 (4.6 MB)
• 7. Batching and early stopping.vtt (2.5 KB)
• 7.1 TensorFlow_MNIST_with_comments_Part_5.html (0.2 KB)
• 8. Learning.mp4 (15.9 MB)
• 8. Learning.vtt (8.9 KB)
• 8.1 TensorFlow_MNIST_with_comments_Part_6.html (0.2 KB)
• 9. Discuss the results and test.mp4 (22.0 MB)
• 9. Discuss the results and test.vtt (7.2 KB)
• 9.1 TensorFlow_MNIST_with_comments.html (0.1 KB)

• 1. Exploring the dataset and identifying predictors.mp4 (23.3 MB)
• 1. Exploring the dataset and identifying predictors.vtt (9.4 KB)
• 1.1 Audiobooks_data.csv.csv (710.8 KB)
• 10. Testing the model.mp4 (4.3 MB)
• 10. Testing the model.vtt (2.3 KB)
• 11. A comment on the homework.mp4 (13.0 MB)
• 11. A comment on the homework.vtt (4.6 KB)
• 11.1 Homework exercise.html (0.1 KB)
• 12. Final exercise.html (0.4 KB)
• 12.1 Homework exercise.html (0.1 KB)
• 2. Outlining the business case solution.mp4 (3.8 MB)
• 2. Outlining the business case solution.vtt (2.2 KB)
• 3. Balancing the dataset.mp4 (13.8 MB)
• 3. Balancing the dataset.vtt (3.9 KB)
• 4. Preprocessing the data.mp4 (34.3 MB)
• 4. Preprocessing the data.vtt (11.8 KB)
• 4.1 Preprocessing.html (0.1 KB)
• 5. Preprocessing exercise.html (0.4 KB)
• 5.1 Preprocessing exercise.html (0.1 KB)
• 6. Create a class for batching.mp4 (27.6 MB)
• 6. Create a class for batching.vtt (6.9 KB)
• 6.1 Class.html (0.1 KB)
• 7. Outlining the model.mp4 (19.5 MB)
• 7. Outlining the model.vtt (6.1 KB)
• 7.1 Outlining the model.html (0.1 KB)
• 8. Optimizing the algorithm.mp4 (12.2 MB)
• 8. Optimizing the algorithm.vtt (5.7 KB)
• 8.1 Optimizing the algorithm.html (0.1 KB)
• 9. Interpreting the result.mp4 (5.4 MB)
• 9. Interpreting the result.vtt (2.6 KB)
• 9.1 Interpreting the result.html (0.1 KB)

• 1. What is a Matrix.mp4 (33.6 MB)
• 1. What is a Matrix.vtt (3.8 KB)
• 10. Dot Product of Matrices.mp4 (49.4 MB)
• 10. Dot Product of Matrices.vtt (8.2 KB)
• 10.1 Dot Product of Matrices Python Notebook.html (0.2 KB)
• 11. Why is Linear Algebra Useful.mp4 (144.3 MB)
• 11. Why is Linear Algebra Useful.vtt (10.3 KB)
• 2. Scalars and Vectors.mp4 (33.8 MB)
• 2. Scalars and Vectors.vtt (3.3 KB)
• 3. Linear Algebra and Geometry.mp4 (49.8 MB)
• 3. Linear Algebra and Geometry.vtt (3.5 KB)
• 4. Scalars, Vectors and Matrices in Python.mp4 (26.7 MB)
• 4. Scalars, Vectors and Matrices in Python.vtt (5.3 KB)
• 4.1 Scalars, Vectors and Matrices Python Notebook.html (0.2 KB)
• 5. Tensors.mp4 (22.5 MB)
• 5. Tensors.vtt (3.2 KB)
• 5.1 Tensors Notebook.html (0.1 KB)
• 6. Addition and Subtraction of Matrices.mp4 (32.6 MB)
• 6. Addition and Subtraction of Matrices.vtt (3.5 KB)
• 6.1 Addition and Subtraction Python Notebook.html (0.2 KB)
• 7. Errors when Adding Matrices.mp4 (11.2 MB)
• 7. Errors when Adding Matrices.vtt (2.3 KB)
• 7.1 Errors when Adding Matrices Python Notebook.html (0.2 KB)
• 8. Transpose of a Matrix.mp4 (38.1 MB)
• 8. Transpose of a Matrix.vtt (4.7 KB)
• 8.1 Transpose of a Matrix Python Notebook.html (0.2 KB)
• 9. Dot Product of Vectors.mp4 (24.0 MB)
• 9. Dot Product of Vectors.vtt (3.7 KB)
• 9.1 Dot Product Python Notebook.html (0.2 KB)

• 1. See how much you have learned.mp4 (14.0 MB)
• 1. See how much you have learned.vtt (4.6 KB)
• 2. What’s further out there in the machine and deep learning world.mp4 (6.3 MB)
• 2. What’s further out there in the machine and deep learning world.vtt (2.3 KB)
• 3. An overview of CNNs.mp4 (10.9 MB)
• 3. An overview of CNNs.vtt (5.7 KB)
• 4. How DeepMind uses deep learning.html (1.4 KB)
• 5. An overview of RNNs.mp4 (4.9 MB)
• 5. An overview of RNNs.vtt (3.2 KB)
• 6. An overview of non-NN approaches.mp4 (7.8 MB)
• 6. An overview of non-NN approaches.vtt (4.6 KB)

• 1. Bonus lecture Next steps.html (2.5 KB)

• 1. Introduction to neural networks.mp4 (13.6 MB)
• 1. Introduction to neural networks.vtt (5.2 KB)
• 1.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 10. The linear model. Multiple inputs.mp4 (7.5 MB)
• 10. The linear model. Multiple inputs.vtt (2.7 KB)
• 10.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 11. The linear model. Multiple inputs - Quiz.html (0.2 KB)
• 12. The linear model. Multiple inputs and multiple outputs.mp4 (38.3 MB)
• 12. The linear model. Multiple inputs and multiple outputs.vtt (4.8 KB)
• 12.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 13. The linear model. Multiple inputs and multiple outputs - Quiz.html (0.2 KB)
• 14. Graphical representation.mp4 (6.4 MB)
• 14. Graphical representation.vtt (2.3 KB)
• 14.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 15. Graphical representation - Quiz.html (0.2 KB)
• 16. The objective function.mp4 (5.7 MB)
• 16. The objective function.vtt (1.8 KB)
• 16.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 17. The objective function - Quiz.html (0.2 KB)
• 18. L2-norm loss.mp4 (7.3 MB)
• 18. L2-norm loss.vtt (2.5 KB)
• 18.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 19. L2-norm loss - Quiz.html (0.2 KB)
• 2. Introduction to neural networks - Quiz.html (0.2 KB)
• 20. Cross-entropy loss.mp4 (11.4 MB)
• 20. Cross-entropy loss.vtt (4.6 KB)
• 20.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 21. Cross-entropy loss - Quiz.html (0.2 KB)
• 22. One parameter gradient descent.mp4 (17.8 MB)
• 22. One parameter gradient descent.vtt (7.4 KB)
• 22.1 GD-function-example.xlsx.xlsx (42.3 KB)
• 22.2 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 23. One parameter gradient descent - Quiz.html (0.2 KB)
• 24. N-parameter gradient descent.mp4 (39.5 MB)
• 24. N-parameter gradient descent.vtt (6.6 KB)
• 24.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 25. N-parameter gradient descent - Quiz.html (0.2 KB)
• 3. Training the model.mp4 (8.8 MB)
• 3. Training the model.vtt (3.8 KB)
• 3.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 4. Training the model - Quiz.html (0.2 KB)
• 5. Types of machine learning.mp4 (12.2 MB)
• 5. Types of machine learning.vtt (4.6 KB)
• 5.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 6. Types of machine learning - Quiz.html (0.2 KB)
• 7. The linear model.mp4 (9.1 MB)
• 7. The linear model.vtt (3.5 KB)
• 7.1 Course Notes - Section 2.pdf.pdf (927.7 KB)
• 8. The linear model - Quiz.html (0.2 KB)
• 9. Need Help with Linear Algebra.html (0.8 KB)

• 1. Setting up the environment - An introduction - Do not skip, please!.mp4 (2.6 MB)
• 1. Setting up the environment - An introduction - Do not skip, please!.vtt (1.1 KB)
• 10. Installing packages - exercise.html (0.2 KB)
• 11. Installing packages - solution.html (0.3 KB)
• 2. Why Python and why Jupyter.mp4 (13.6 MB)
• 2. Why Python and why Jupyter.vtt (5.6 KB)
• 3. Why Python and why Jupyter - Quiz.html (0.2 KB)
• 4. Installing Anaconda.mp4 (9.4 MB)
• 4. Installing Anaconda.vtt (4.1 KB)
• 5. The Jupyter dashboard - part 1.mp4 (5.6 MB)
• 5. The Jupyter dashboard - part 1.vtt (2.8 KB)
• 6. The Jupyter dashboard - part 2.mp4 (10.9 MB)
• 6. The Jupyter dashboard - part 2.vtt (6.0 KB)
• 7. Jupyter Shortcuts.html (0.3 KB)
• 7.1 Shortcuts for Jupyter.pdf.pdf (619.2 KB)
• 8. The Jupyter dashboard - Quiz.html (0.2 KB)
• 9. Installing the TensorFlow package.mp4 (4.9 MB)
• 9. Installing the TensorFlow package.vtt (2.8 KB)

• 1. Minimal example - part 1.mp4 (6.5 MB)
• 1. Minimal example - part 1.vtt (3.9 KB)
• 1.1 Minimal example Part 1.html (0.1 KB)
• 2. Minimal example - part 2.mp4 (10.7 MB)
• 2. Minimal example - part 2.vtt (5.9 KB)
• 2.1 Minimal example - part 2.html (0.1 KB)
• 3. Minimal example - part 3.mp4 (9.8 MB)
• 3. Minimal example - part 3.vtt (3.9 KB)
• 3.1 Minimal example - part 3.html (0.1 KB)
• 4. Minimal example - part 4.mp4 (20.8 MB)
• 4. Minimal example - part 4.vtt (9.5 KB)
• 4.1 Minimal example - part 4.html (0.1 KB)
• 5. Minimal example - Exercises.html (1.6 KB)
• 5.1 Minimal_example_Exercise_2_Solution.html (0.1 KB)
• 5.10 Minimal_example_Exercise_6_Solution.html (0.1 KB)
• 5.2 Minimal_example_Exercise_3.d. Solution.html (0.2 KB)
• 5.3 Minimal_example_Exercise_4_Solution.html (0.1 KB)
• 5.4 Minimal_example_Exercise_3.b. Solution.html (0.2 KB)
• 5.5 Minimal_example_All_Exercises.html (0.1 KB)
• 5.6 Minimal_example_Exercise_1_Solution.html (0.1 KB)
• 5.7 Minimal_example_Exercise_3.c. Solution.html (0.2 KB)
• 5.8 Minimal_example_Exercise_5_Solution.html (0.1 KB)
• 5.9 Minimal_example_Exercise_3.a. Solution.html (0.2 KB)

• 1. TensorFlow outline.mp4 (14.5 MB)
• 1. TensorFlow outline.vtt (4.6 KB)
• 2. TensorFlow intro.mp4 (7.5 MB)
• 2. TensorFlow intro.vtt (1.9 KB)
• 3. Types of file formats in TensorFlow.mp4 (5.8 MB)
• 3. Types of file formats in TensorFlow.vtt (3.0 KB)
• 3.1 TensorFlow Minimal example - Part 1.html (0.2 KB)
• 4. Inputs, outputs, targets, weights, biases - model layout.mp4 (13.0 MB)
• 4. Inputs, outputs, targets, weights, biases - model layout.vtt (6.4 KB)
• 4.1 TensorFlow Minimal example - Part 2.html (0.2 KB)
• 5. Loss function and gradient descent - introducing optimizers.mp4 (9.7 MB)
• 5. Loss function and gradient descent - introducing optimizers.vtt (4.2 KB)
• 5.1 TensorFlow Minimal example - Part 3.html (0.2 KB)
• 6. Model output.mp4 (14.3 MB)
• 6. Model output.vtt (6.9 KB)
• 6.1 TensorFlow - Minimal example complete.html (0.2 KB)
• 7. Minimal example - Exercises.html (1.6 KB)
• 7.1 TensorFlow_Minimal_Example_Exercise_1_Solution.html (0.2 KB)
• 7.2 TensorFlow_Minimal_Example_Exercise_2_3_Solution.html (0.2 KB)
• 7.3 TensorFlow_Minimal_Example_Exercise_2_1_Solution.html (0.2 KB)
• 7.4 TensorFlow_Minimal_Example_All_Exercises.html (0.2 KB)
• 7.5 TensorFlow_Minimal_Example_Exercise_3_Solution.html (0.2 KB)
• 7.6 TensorFlow_Minimal_Example_Exercise_2_2_Solution.html (0.2 KB)
• 7.7 TensorFlow_Minimal_Example_Exercise_4_Solution.html (0.2 KB)
• 7.8 TensorFlow_Minimal_Example_Exercise_2_4_Solution.html (0.2 KB)

• 1. Layers.mp4 (4.7 MB)
• 1. Layers.vtt (2.2 KB)
• 1.1 Course Notes - Section 6.pdf.pdf (936.4 KB)
• 2. What is a deep net.mp4 (6.7 MB)
• 2. What is a deep net.vtt (2.9 KB)
• 2.1 Course Notes - Section 6.pdf.pdf (936.4 KB)
• 3. Understanding deep nets in depth.mp4 (13.4 MB)
• 3. Understanding deep nets in depth.vtt (5.8 KB)
• 4. Why do we need non-linearities.mp4 (9.0 MB)
• 4. Why do we need non-linearities.vtt (3.3 KB)
• 5. Activation functions.mp4 (8.7 MB)
• 5. Activation functions.vtt (4.5 KB)
• 6. Softmax activation.mp4 (7.4 MB)
• 6. Softmax activation.vtt (7.4 MB)
• 7. Backpropagation.mp4 (11.1 MB)
• 7. Backpropagation.vtt (6.5 MB)
• 8. Backpropagation - visual representation.mp4 (6.8 MB)
• 8. Backpropagation - visual representation.vtt (3.5 KB)

• 1. Backpropagation. A peek into the Mathematics of Optimization.html (0.5 KB)
• 1.1 Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf.pdf (182.4 KB)

• 1. Underfitting and overfitting.mp4 (11.1 MB)
• 1. Underfitting and overfitting.vtt (5.0 KB)
• 2. Underfitting and overfitting - classification.mp4 (6.8 MB)
• 2. Underfitting and overfitting - classification.vtt (2.4 KB)
• 3. Training and validation.mp4 (9.2 MB)
• 3. Training and validation.vtt (4.2 KB)
• 4. Training, validation, and test.mp4 (7.4 MB)
• 4. Training, validation, and test.vtt (3.1 KB)
• 5. N-fold cross validation.mp4 (7.0 MB)
• 5. N-fold cross validation.vtt (3.7 KB)
• 6. Early stopping.mp4 (9.4 MB)
• 6. Early stopping.vtt (6.0 KB)

• 1. Initialization - Introduction.mp4 (8.0 MB)
• 1. Initialization - Introduction.vtt (3.1 KB)
• 2. Types of simple initializations.mp4 (5.6 MB)
• 2. Types of simple initializations.vtt (3.2 KB)
• 3. Xavier initialization.mp4 (5.8 MB)
• 3. Xavier initialization.vtt (3.2 KB)

• [CourseClub.Me].url (0.0 KB)
• [DesireCourse.Net].url (0.0 KB)