Tutorialsplanet NET Udemy Deep Learning with TensorFlow 2020 | AF3A5895ECC7A288538C1CBCD14F00A0DE0DD699

Tutorialsplanet NET Udemy Deep Learning with TensorFlow 2020

Name	[Tutorialsplanet.NET] Udemy - Deep Learning with TensorFlow 2.0 [2020]	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	2.0 GB
Total Files	299
Hash	AF3A5895ECC7A288538C1CBCD14F00A0DE0DD699

/1. Welcome! Course introduction/
1. Meet your instructors and why you should study machine learning.mp4	110.9 MB
1. Meet your instructors and why you should study machine learning.srt	10.4 KB
2. What does the course cover.mp4	17.1 MB
2. What does the course cover.srt	6.4 KB
3. What does the course cover - Quiz.html	0.2 KB
4. Download All Resources and Important FAQ.html	0.7 KB
/10. Gradient descent and learning rates/
1. Stochastic gradient descent.mp4	9.8 MB
1. Stochastic gradient descent.srt	5.0 KB
2. Gradient descent pitfalls.mp4	4.5 MB
2. Gradient descent pitfalls.srt	2.9 KB
3. Momentum.mp4	6.4 MB
3. Momentum.srt	3.6 KB
4. Learning rate schedules.mp4	10.8 MB
4. Learning rate schedules.srt	6.1 KB
5. Learning rate schedules. A picture.mp4	3.3 MB
5. Learning rate schedules. A picture.srt	2.2 KB
6. Adaptive learning rate schedules.mp4	9.3 MB
6. Adaptive learning rate schedules.srt	5.3 KB
7. Adaptive moment estimation.mp4	8.1 MB
7. Adaptive moment estimation.srt	3.4 KB
/11. Preprocessing/
1. Preprocessing introduction.mp4	8.8 MB
1. Preprocessing introduction.srt	3.9 KB
2. Basic preprocessing.mp4	3.8 MB
2. Basic preprocessing.srt	1.7 KB
3. Standardization.mp4	8.7 MB
3. Standardization.srt	6.1 KB
4. Dealing with categorical data.mp4	6.4 MB
4. Dealing with categorical data.srt	2.8 KB
5. One-hot and binary encoding.mp4	6.5 MB
5. One-hot and binary encoding.srt	4.9 KB
/12. The MNIST example/
1. The dataset.mp4	14.0 MB
1. The dataset.srt	3.7 KB
10. Learning.mp4	42.9 MB
10. Learning.srt	8.1 KB
10.1 TensorFlow MNIST - Part 6 with comments.html	0.2 KB
11. MNIST - exercises.html	2.0 KB
11.1 TensorFlow MNIST - All Exercises.html	0.1 KB
12. MNIST - solutions.html	2.2 KB
12.1 3. TensorFlow MNIST - Exercise 3 Solution.html	0.2 KB
12.10 7. TensorFlow MNIST - Exercise 7 Solution.html	0.2 KB
12.2 1. TensorFlow MNIST - Exercise 1 Solution.html	0.2 KB
12.3 2. TensorFlow MNIST - Exercise 2 Solution.html	0.2 KB
12.4 4. TensorFlow MNIST - Exercise 4 Solution.html	0.2 KB
12.5 5. TensorFlow MNIST - Exercise 5 Solution.html	0.2 KB
12.6 8. TensorFlow MNIST - Exercise 8 Solution.html	0.2 KB
12.7 10. TensorFlow MNIST - Exercise 10 Solution.html	0.2 KB
12.8 9. TensorFlow MNIST - Exercise 9 Solution.html	0.2 KB
12.9 6. TensorFlow MNIST - Exercise 6 Solution.html	0.2 KB
13. Testing the model.mp4	31.0 MB
13. Testing the model.srt	6.2 KB
13.1 TensorFlow MNIST - Complete Code.html	0.1 KB
13.2 TensorFlow MNIST - Complete Code with Comments.html	0.2 KB
2. How to tackle the MNIST.mp4	19.6 MB
2. How to tackle the MNIST.srt	3.6 KB
3. Importing the relevant packages and load the data.mp4	17.1 MB
3. Importing the relevant packages and load the data.srt	3.1 KB
3.1 TensorFlow MNIST - Part 1 with comments.html	0.2 KB
4. Preprocess the data - create a validation dataset and scale the data.mp4	30.5 MB
4. Preprocess the data - create a validation dataset and scale the data.srt	6.4 KB
5. Preprocess the data - scale the test data.html	0.1 KB
5.1 TensorFlow MNIST - Part 2 with comments.html	0.2 KB
6. Preprocess the data - shuffle and batch the data.mp4	43.6 MB
6. Preprocess the data - shuffle and batch the data.srt	9.5 KB
7. Preprocess the data - shuffle and batch the data.html	0.1 KB
7.1 TensorFlow MNIST - Part 3 with comments.html	0.2 KB
8. Outline the model.mp4	29.6 MB
8. Outline the model.srt	7.4 KB
8.1 TensorFlow MNIST - Part 4 with comments.html	0.2 KB
9. Select the loss and the optimizer.mp4	14.6 MB
9. Select the loss and the optimizer.srt	3.1 KB
9.1 TensorFlow MNIST - Part 5 with comments.html	0.2 KB
/13. Business case/
1. Exploring the dataset and identifying predictors.mp4	69.5 MB
1. Exploring the dataset and identifying predictors.srt	10.9 KB
1.1 Audiobooks_data.csv	640.2 KB
10. Setting an early stopping mechanism - Exercise.html	0.2 KB
11. Testing the model.mp4	11.3 MB
11. Testing the model.srt	2.1 KB
11.1 TensorFlow Business Case - Machine Learning Complete Code with Comments.html	0.2 KB
12. Final exercise.html	0.4 KB
12.1 TensorFlow Business Case - Machine Learning Complete Code with Comments.html	0.2 KB
2. Outlining the business case solution.mp4	7.7 MB
2. Outlining the business case solution.srt	2.0 KB
3. Balancing the dataset.mp4	31.9 MB
3. Balancing the dataset.srt	4.6 KB
4. Preprocessing the data.mp4	88.4 MB
4. Preprocessing the data.srt	12.6 KB
4.1 TensorFlow Business Case - Preprocessing.html	0.1 KB
4.2 TensorFlow Business Case - Preprocessing with Comments.html	0.2 KB
4.3 Audiobooks_data.csv	640.2 KB
5. Preprocessing exercise.html	0.4 KB
5.1 TensorFlow Business Case - Preprocessing Exercise.html	0.2 KB
5.2 TensorFlow Business Case - Preprocessing Exercise Solution.html	0.2 KB
5.3 Audiobooks_data.csv	640.2 KB
6. Load the preprocessed data.mp4	18.4 MB
6. Load the preprocessed data.srt	4.8 KB
7. Load the preprocessed data - Exercise.html	0.1 KB
7.1 TensorFlow Business Case - Machine Learning - Part 1.html	0.2 KB
8. Learning and interpreting the result.mp4	32.7 MB
8. Learning and interpreting the result.srt	6.4 KB
8.1 TensorFlow Business Case - Machine Learning - Part 2.html	0.2 KB
9. Setting an early stopping mechanism.mp4	52.2 MB
9. Setting an early stopping mechanism.srt	8.0 KB
9.1 TensorFlow Business Case - Machine Learning - Part 3.html	0.2 KB
/14. Appendix Linear Algebra Fundamentals/
1. What is a Matrix.mp4	35.2 MB
1. What is a Matrix.srt	4.4 KB
10. Dot Product of Matrices.mp4	51.8 MB
10. Dot Product of Matrices.srt	9.7 KB
10.1 Dot Product of Matrices Python Notebook.html	0.2 KB
11. Why is Linear Algebra Useful.mp4	151.3 MB
11. Why is Linear Algebra Useful.srt	12.1 KB
2. Scalars and Vectors.mp4	35.5 MB
2. Scalars and Vectors.srt	3.9 KB
3. Linear Algebra and Geometry.mp4	52.2 MB
3. Linear Algebra and Geometry.srt	4.2 KB
4. Scalars, Vectors and Matrices in Python.mp4	28.0 MB
4. Scalars, Vectors and Matrices in Python.srt	6.3 KB
4.1 Scalars, Vectors and Matrices Python Notebook.html	0.2 KB
5. Tensors.mp4	23.6 MB
5. Tensors.srt	3.7 KB
5.1 Tensors Notebook.html	0.1 KB
6. Addition and Subtraction of Matrices.mp4	34.2 MB
6. Addition and Subtraction of Matrices.srt	4.1 KB
6.1 Addition and Subtraction Python Notebook.html	0.2 KB
7. Errors when Adding Matrices.mp4	11.7 MB
7. Errors when Adding Matrices.srt	2.6 KB
7.1 Errors when Adding Matrices Python Notebook.html	0.2 KB
8. Transpose of a Matrix.mp4	39.9 MB
8. Transpose of a Matrix.srt	5.5 KB
8.1 Transpose of a Matrix Python Notebook.html	0.2 KB
9. Dot Product of Vectors.mp4	25.1 MB
9. Dot Product of Vectors.srt	4.4 KB
9.1 Dot Product Python Notebook.html	0.2 KB
/15. Conclusion/
1. See how much you have learned.mp4	14.6 MB
1. See how much you have learned.srt	5.3 KB
2. What’s further out there in the machine and deep learning world.mp4	6.6 MB
2. What’s further out there in the machine and deep learning world.srt	2.6 KB
3. An overview of CNNs.mp4	11.5 MB
3. An overview of CNNs.srt	6.6 KB
4. How DeepMind uses deep learning.html	1.4 KB
5. An overview of RNNs.mp4	5.1 MB
5. An overview of RNNs.srt	3.7 KB
6. An overview of non-NN approaches.mp4	8.2 MB
6. An overview of non-NN approaches.srt	5.3 KB
/16. Bonus lecture/
1. Bonus lecture Next steps.html	2.6 KB
/2. Introduction to neural networks/
1. Introduction to neural networks.mp4	14.2 MB
1. Introduction to neural networks.srt	6.1 KB
1.1 Course Notes - Section 2.pdf	949.9 KB
10. The linear model. Multiple inputs.mp4	7.9 MB
10. The linear model. Multiple inputs.srt	3.2 KB
10.1 Course Notes - Section 2.pdf	949.9 KB
11. The linear model. Multiple inputs - Quiz.html	0.2 KB
12. The linear model. Multiple inputs and multiple outputs.mp4	40.1 MB
12. The linear model. Multiple inputs and multiple outputs.srt	5.6 KB
12.1 Course Notes - Section 2.pdf	949.9 KB
13. The linear model. Multiple inputs and multiple outputs - Quiz.html	0.2 KB
14. Graphical representation.mp4	6.7 MB
14. Graphical representation.srt	2.8 KB
14.1 Course Notes - Section 2.pdf	949.9 KB
15. Graphical representation - Quiz.html	0.2 KB
16. The objective function.mp4	6.0 MB
16. The objective function.srt	2.1 KB
16.1 Course Notes - Section 2.pdf	949.9 KB
17. The objective function - Quiz.html	0.2 KB
18. L2-norm loss.mp4	7.6 MB
18. L2-norm loss.srt	2.9 KB
18.1 Course Notes - Section 2.pdf	949.9 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	11.9 MB
20. Cross-entropy loss.srt	5.5 KB
20.1 Course Notes - Section 2.pdf	949.9 KB
21. Cross-entropy loss - Quiz.html	0.2 KB
22. One parameter gradient descent.mp4	18.6 MB
22. One parameter gradient descent.srt	8.7 KB
22.1 Course Notes - Section 2.pdf	949.9 KB
22.2 GD-function-example.xlsx	43.4 KB
23. One parameter gradient descent - Quiz.html	0.2 KB
24. N-parameter gradient descent.mp4	41.4 MB
24. N-parameter gradient descent.srt	7.7 KB
24.1 Course Notes - Section 2.pdf	949.9 KB
25. N-parameter gradient descent - Quiz.html	0.2 KB
3. Training the model.mp4	9.2 MB
3. Training the model.srt	4.4 KB
3.1 Course Notes - Section 2.pdf	949.9 KB
4. Training the model - Quiz.html	0.2 KB
5. Types of machine learning.mp4	12.8 MB
5. Types of machine learning.srt	5.4 KB
5.1 Course Notes - Section 2.pdf	949.9 KB
6. Types of machine learning - Quiz.html	0.2 KB
7. The linear model.mp4	9.6 MB
7. The linear model.srt	4.0 KB
7.1 Course Notes - Section 2.pdf	949.9 KB
8. The linear model - Quiz.html	0.2 KB
9. Need Help with Linear Algebra.html	0.8 KB
/3. Setting up the working environment/
1. Setting up the environment - An introduction - Do not skip, please!.mp4	6.2 MB
1. Setting up the environment - An introduction - Do not skip, please!.srt	1.4 KB
10. Installing packages - exercise.html	0.2 KB
11. Installing packages - solution.html	0.3 KB
2. Why Python and why Jupyter.mp4	33.6 MB
2. Why Python and why Jupyter.srt	6.5 KB
3. Why Python and why Jupyter - Quiz.html	0.2 KB
4. Installing Anaconda.mp4	29.8 MB
4. Installing Anaconda.srt	4.7 KB
5. The Jupyter dashboard - part 1.mp4	9.1 MB
5. The Jupyter dashboard - part 1.srt	3.2 KB
6. The Jupyter dashboard - part 2.mp4	19.7 MB
6. The Jupyter dashboard - part 2.srt	6.9 KB
7. Jupyter Shortcuts.html	0.3 KB
7.1 Shortcuts for Jupyter.pdf	634.0 KB
8. The Jupyter dashboard - Quiz.html	0.2 KB
9. Installing TensorFlow 2.mp4	40.6 MB
9. Installing TensorFlow 2.srt	6.5 KB
/4. Minimal example - your first machine learning algorithm/
1. Minimal example - part 1.mp4	6.9 MB
1. Minimal example - part 1.srt	4.6 KB
1.1 Minimal example Part 1.html	0.1 KB
2. Minimal example - part 2.mp4	11.2 MB
2. Minimal example - part 2.srt	7.0 KB
2.1 Minimal example - part 2.html	0.1 KB
3. Minimal example - part 3.mp4	10.2 MB
3. Minimal example - part 3.srt	4.6 KB
3.1 Minimal example - part 3.html	0.1 KB
4. Minimal example - part 4.mp4	21.8 MB
4. Minimal example - part 4.srt	11.1 KB
4.1 Minimal example - part 4.html	0.1 KB
5. Minimal example - Exercises.html	1.6 KB
5.1 Minimal_example_Exercise_6_Solution.html	0.1 KB
5.10 Minimal_example_All_Exercises.html	0.1 KB
5.2 Minimal_example_Exercise_3.c. Solution.html	0.2 KB
5.3 Minimal_example_Exercise_4_Solution.html	0.1 KB
5.4 Minimal_example_Exercise_3.a. Solution.html	0.2 KB
5.5 Minimal_example_Exercise_5_Solution.html	0.1 KB
5.6 Minimal_example_Exercise_1_Solution.html	0.1 KB
5.7 Minimal_example_Exercise_3.d. Solution.html	0.2 KB
5.8 Minimal_example_Exercise_3.b. Solution.html	0.2 KB
5.9 Minimal_example_Exercise_2_Solution.html	0.1 KB
/5. TensorFlow - An introduction/
1. TensorFlow outline.mp4	35.2 MB
1. TensorFlow outline.srt	5.4 KB
2. TensorFlow 2 intro.mp4	23.1 MB
2. TensorFlow 2 intro.srt	3.7 KB
3. A Note on Coding in TensorFlow.mp4	7.1 MB
3. A Note on Coding in TensorFlow.srt	1.4 KB
4. Types of file formats in TensorFlow and data handling.mp4	17.2 MB
4. Types of file formats in TensorFlow and data handling.srt	3.6 KB
4.1 TensorFlow Minimal Example - Part 1.html	0.1 KB
5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4	36.4 MB
5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.srt	8.0 KB
5.1 TensorFlow Minimal Example - Part 2.html	0.1 KB
6. Interpreting the result and extracting the weights and bias.mp4	31.7 MB
6. Interpreting the result and extracting the weights and bias.srt	6.3 KB
6.1 TensorFlow Minimal Example - Part 3.html	0.1 KB
7. Cutomizing your model.mp4	24.0 MB
7. Cutomizing your model.srt	4.2 KB
7.1 TensorFlow Minimal Example - Complete Code with Comments.html	0.2 KB
7.2 TensorFlow Minimal Example - Complete Code.html	0.1 KB
8. Minimal example with TensorFlow - Exercises.html	1.4 KB
8.1 TensorFlow Minimal Example - Exercise 2_2 - Solution.html	0.2 KB
8.2 TensorFlow Minimal Example - Exercise 1 - Solution.html	0.2 KB
8.3 TensorFlow Minimal Example - Exercise 3 - Solution.html	0.2 KB
8.4 TensorFlow Minimal Example - Exercise 2_1 - Solution.html	0.2 KB
8.5 TensorFlow Minimal Example - All Exercises.html	0.2 KB
/6. Going deeper Introduction to deep neural networks/
1. Layers.mp4	5.0 MB
1. Layers.srt	2.5 KB
1.1 Course Notes - Section 6.pdf	958.9 KB
2. What is a deep net.mp4	7.1 MB
2. What is a deep net.srt	3.4 KB
2.1 Course Notes - Section 6.pdf	958.9 KB
3. Understanding deep nets in depth.mp4	14.0 MB
3. Understanding deep nets in depth.srt	6.8 KB
4. Why do we need non-linearities.mp4	9.4 MB
4. Why do we need non-linearities.srt	3.9 KB
5. Activation functions.mp4	9.2 MB
5. Activation functions.srt	5.3 KB
6. Softmax activation.mp4	7.7 MB
6. Softmax activation.srt	4.4 KB
7. Backpropagation.mp4	11.6 MB
7. Backpropagation.srt	4.5 KB
8. Backpropagation - visual representation.mp4	7.2 MB
8. Backpropagation - visual representation.srt	4.1 KB
/7. Backpropagation. A peek into the Mathematics of Optimization/
1. Backpropagation. A peek into the Mathematics of Optimization.html	0.5 KB
1.1 Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf	186.8 KB
/8. Overfitting/
1. Underfitting and overfitting.mp4	11.6 MB
1. Underfitting and overfitting.srt	5.8 KB
2. Underfitting and overfitting - classification.mp4	7.1 MB
2. Underfitting and overfitting - classification.srt	2.8 KB
3. Training and validation.mp4	9.7 MB
3. Training and validation.srt	5.0 KB
4. Training, validation, and test.mp4	7.8 MB
4. Training, validation, and test.srt	3.6 KB
5. N-fold cross validation.mp4	7.3 MB
5. N-fold cross validation.srt	4.3 KB
6. Early stopping.mp4	9.9 MB
6. Early stopping.srt	7.0 KB
/9. Initialization/
1. Initialization - Introduction.mp4	8.4 MB
1. Initialization - Introduction.srt	3.6 KB
2. Types of simple initializations.mp4	5.9 MB
2. Types of simple initializations.srt	3.8 KB
3. Xavier initialization.mp4	6.1 MB
3. Xavier initialization.srt	3.8 KB
/
[Tutorialsplanet.NET].url	0.1 KB
Total files 299