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

seeders: 0 leechers: 1 updated: 7 months ago
Added 6 years ago by CourseClub in Other
Downloaded 2 times.
1337x.to
Udemy - Master Deep Learning with TensorFlow in Python [DC]

Torrent Contents Size: 1.4 GB

Udemy - Master Deep Learning with TensorFlow in Python [DC]
▼ show more 281 files
1. Backpropagation. A peek into the Mathematics of Optimization.html
HTML
512 B
1. Bonus lecture Next steps.html
HTML
2.5 KB
1. Exploring the dataset and identifying predictors.mp4
MP4
23.3 MB
1. Exploring the dataset and identifying predictors.vtt
VTT
9.4 KB
1. Initialization - Introduction.mp4
MP4
8 MB
1. Initialization - Introduction.vtt
VTT
3.1 KB
1. Introduction to neural networks.mp4
MP4
13.6 MB
1. Introduction to neural networks.vtt
VTT
5.2 KB
1. Layers.mp4
MP4
4.7 MB
1. Layers.vtt
VTT
2.2 KB
1. Meet your instructors and why you should study machine learning.mp4
MP4
105.8 MB
1. Meet your instructors and why you should study machine learning.vtt
VTT
8.8 KB
1. Minimal example - part 1.mp4
MP4
6.5 MB
1. Minimal example - part 1.vtt
VTT
3.9 KB
1. Preprocessing introduction.mp4
MP4
8.4 MB
1. Preprocessing introduction.vtt
VTT
3.4 KB
1. See how much you have learned.mp4
MP4
14 MB
1. See how much you have learned.vtt
VTT
4.6 KB
1. Setting up the environment - An introduction - Do not skip, please!.mp4
MP4
2.6 MB
1. Setting up the environment - An introduction - Do not skip, please!.vtt
VTT
1.1 KB
1. Stochastic gradient descent.mp4
MP4
9.4 MB
1. Stochastic gradient descent.vtt
VTT
4.2 KB
1. TensorFlow outline.mp4
MP4
14.5 MB
1. TensorFlow outline.vtt
VTT
4.6 KB
1. The dataset.mp4
MP4
7.4 MB
1. The dataset.vtt
VTT
3.1 KB
1. Underfitting and overfitting.mp4
MP4
11.1 MB
1. Underfitting and overfitting.vtt
VTT
5 KB
1. What is a Matrix.mp4
MP4
33.6 MB
1. What is a Matrix.vtt
VTT
3.8 KB
1.1 Audiobooks_data.csv.csv
CSV
710.8 KB
1.1 Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf.pdf
PDF
182.4 KB
1.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
1.1 Course Notes - Section 6.pdf.pdf
PDF
936.4 KB
1.1 Minimal example Part 1.html
HTML
102.4 B
10. Dot Product of Matrices.mp4
MP4
49.4 MB
10. Dot Product of Matrices.vtt
VTT
8.2 KB
10. Installing packages - exercise.html
HTML
204.8 B
10. MNIST - exercises.html
HTML
2.3 KB
10. Testing the model.mp4
MP4
4.3 MB
10. Testing the model.vtt
VTT
2.3 KB
10. The linear model. Multiple inputs.mp4
MP4
7.5 MB
10. The linear model. Multiple inputs.vtt
VTT
2.7 KB
10.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
10.1 Dot Product of Matrices Python Notebook.html
HTML
204.8 B
10.1 MNIST_Exercises_All.html
HTML
102.4 B
11. A comment on the homework.mp4
MP4
13 MB
11. A comment on the homework.vtt
VTT
4.6 KB
11. Installing packages - solution.html
HTML
307.2 B
11. MNIST - solutions.html
HTML
2.2 KB
11. The linear model. Multiple inputs - Quiz.html
HTML
204.8 B
11. Why is Linear Algebra Useful.mp4
MP4
144.3 MB
11. Why is Linear Algebra Useful.vtt
VTT
10.3 KB
11.1 Homework exercise.html
HTML
102.4 B
11.1 MNIST_Depth_Solution.html
HTML
102.4 B
11.10 MNIST_Learning_rate_Part_1_Solution.html
HTML
204.8 B
11.11 TensorFlow_MNIST_Activation_functions_Part_1_Solution.html
HTML
204.8 B
11.2 MNIST_take_note_of_time_Solution.html
HTML
204.8 B
11.3 Width_and_Depth_Solution.html
HTML
204.8 B
11.4 MNIST_Learning_rate_Part_2_Solution.html
HTML
204.8 B
11.5 MNIST_around_98_percent_accuracy_solution.html
HTML
204.8 B
11.6 MNIST_Batch_size_Part_2_Solution.html
HTML
204.8 B
11.7 MNIST_Width_Solution.html
HTML
102.4 B
11.8 MNIST_Batch_size_Part_1_Solution.html
HTML
204.8 B
11.9 MNIST_Activation_functions_Part_2_Solution.html
HTML
204.8 B
12. Final exercise.html
HTML
409.6 B
12. The linear model. Multiple inputs and multiple outputs.mp4
MP4
38.3 MB
12. The linear model. Multiple inputs and multiple outputs.vtt
VTT
4.8 KB
12.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
12.1 Homework exercise.html
HTML
102.4 B
13. The linear model. Multiple inputs and multiple outputs - Quiz.html
HTML
204.8 B
14. Graphical representation.mp4
MP4
6.4 MB
14. Graphical representation.vtt
VTT
2.3 KB
14.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
15. Graphical representation - Quiz.html
HTML
204.8 B
16. The objective function.mp4
MP4
5.7 MB
16. The objective function.vtt
VTT
1.8 KB
16.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
17. The objective function - Quiz.html
HTML
204.8 B
18. L2-norm loss.mp4
MP4
7.3 MB
18. L2-norm loss.vtt
VTT
2.5 KB
18.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
19. L2-norm loss - Quiz.html
HTML
204.8 B
2. Basic preprocessing.mp4
MP4
3.7 MB
2. Basic preprocessing.vtt
VTT
1.5 KB
2. Gradient descent pitfalls.mp4
MP4
4.3 MB
2. Gradient descent pitfalls.vtt
VTT
2.5 KB
2. How to tackle the MNIST.mp4
MP4
7.3 MB
2. How to tackle the MNIST.vtt
VTT
3.2 KB
2. Introduction to neural networks - Quiz.html
HTML
204.8 B
2. Minimal example - part 2.mp4
MP4
10.7 MB
2. Minimal example - part 2.vtt
VTT
5.9 KB
2. Outlining the business case solution.mp4
MP4
3.8 MB
2. Outlining the business case solution.vtt
VTT
2.2 KB
2. Scalars and Vectors.mp4
MP4
33.8 MB
2. Scalars and Vectors.vtt
VTT
3.3 KB
2. TensorFlow intro.mp4
MP4
7.5 MB
2. TensorFlow intro.vtt
VTT
1.9 KB
2. Types of simple initializations.mp4
MP4
5.6 MB
2. Types of simple initializations.vtt
VTT
3.2 KB
2. Underfitting and overfitting - classification.mp4
MP4
6.8 MB
2. Underfitting and overfitting - classification.vtt
VTT
2.4 KB
2. What does the course cover.mp4
MP4
16.4 MB
2. What does the course cover.vtt
VTT
5.5 KB
2. What is a deep net.mp4
MP4
6.7 MB
2. What is a deep net.vtt
VTT
2.9 KB
2. What’s further out there in the machine and deep learning world.mp4
MP4
6.3 MB
2. What’s further out there in the machine and deep learning world.vtt
VTT
2.3 KB
2. Why Python and why Jupyter.mp4
MP4
13.6 MB
2. Why Python and why Jupyter.vtt
VTT
5.6 KB
2.1 Course Notes - Section 6.pdf.pdf
PDF
936.4 KB
2.1 Minimal example - part 2.html
HTML
102.4 B
20. Cross-entropy loss.mp4
MP4
11.4 MB
20. Cross-entropy loss.vtt
VTT
4.6 KB
20.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
21. Cross-entropy loss - Quiz.html
HTML
204.8 B
22. One parameter gradient descent.mp4
MP4
17.8 MB
22. One parameter gradient descent.vtt
VTT
7.4 KB
22.1 GD-function-example.xlsx.xlsx
XLSX
42.3 KB
22.2 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
23. One parameter gradient descent - Quiz.html
HTML
204.8 B
24. N-parameter gradient descent.mp4
MP4
39.5 MB
24. N-parameter gradient descent.vtt
VTT
6.6 KB
24.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
25. N-parameter gradient descent - Quiz.html
HTML
204.8 B
3. An overview of CNNs.mp4
MP4
10.9 MB
3. An overview of CNNs.vtt
VTT
5.7 KB
3. Balancing the dataset.mp4
MP4
13.8 MB
3. Balancing the dataset.vtt
VTT
3.9 KB
3. Importing the relevant packages.mp4
MP4
5.5 MB
3. Importing the relevant packages.vtt
VTT
1.9 KB
3. Linear Algebra and Geometry.mp4
MP4
49.8 MB
3. Linear Algebra and Geometry.vtt
VTT
3.5 KB
3. Minimal example - part 3.mp4
MP4
9.8 MB
3. Minimal example - part 3.vtt
VTT
3.9 KB
3. Momentum.mp4
MP4
6.1 MB
3. Momentum.vtt
VTT
3.1 KB
3. Standardization.mp4
MP4
8.3 MB
3. Standardization.vtt
VTT
5.3 KB
3. Training and validation.mp4
MP4
9.2 MB
3. Training and validation.vtt
VTT
4.2 KB
3. Training the model.mp4
MP4
8.8 MB
3. Training the model.vtt
VTT
3.8 KB
3. Types of file formats in TensorFlow.mp4
MP4
5.8 MB
3. Types of file formats in TensorFlow.vtt
VTT
3 KB
3. Understanding deep nets in depth.mp4
MP4
13.4 MB
3. Understanding deep nets in depth.vtt
VTT
5.8 KB
3. What does the course cover - Quiz.html
HTML
204.8 B
3. Why Python and why Jupyter - Quiz.html
HTML
204.8 B
3. Xavier initialization.mp4
MP4
5.8 MB
3. Xavier initialization.vtt
VTT
3.2 KB
3.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
3.1 Minimal example - part 3.html
HTML
102.4 B
3.1 TensorFlow Minimal example - Part 1.html
HTML
204.8 B
3.1 TensorFlow_MNIST_with_comments_Part_1.html
HTML
204.8 B
4. Dealing with categorical data.mp4
MP4
6.1 MB
4. Dealing with categorical data.vtt
VTT
2.4 KB
4. How DeepMind uses deep learning.html
HTML
1.4 KB
4. Inputs, outputs, targets, weights, biases - model layout.mp4
MP4
13 MB
4. Inputs, outputs, targets, weights, biases - model layout.vtt
VTT
6.4 KB
4. Installing Anaconda.mp4
MP4
9.4 MB
4. Installing Anaconda.vtt
VTT
4.1 KB
4. Learning rate schedules.mp4
MP4
10.3 MB
4. Learning rate schedules.vtt
VTT
5.3 KB
4. Minimal example - part 4.mp4
MP4
20.8 MB
4. Minimal example - part 4.vtt
VTT
9.5 KB
4. Outlining the model.mp4
MP4
18.4 MB
4. Outlining the model.vtt
VTT
7.8 KB
4. Preprocessing the data.mp4
MP4
34.3 MB
4. Preprocessing the data.vtt
VTT
11.8 KB
4. Scalars, Vectors and Matrices in Python.mp4
MP4
26.7 MB
4. Scalars, Vectors and Matrices in Python.vtt
VTT
5.3 KB
4. Training the model - Quiz.html
HTML
204.8 B
4. Training, validation, and test.mp4
MP4
7.4 MB
4. Training, validation, and test.vtt
VTT
3.1 KB
4. Why do we need non-linearities.mp4
MP4
9 MB
4. Why do we need non-linearities.vtt
VTT
3.3 KB
4.1 Minimal example - part 4.html
HTML
102.4 B
4.1 Preprocessing.html
HTML
102.4 B
4.1 Scalars, Vectors and Matrices Python Notebook.html
HTML
204.8 B
4.1 TensorFlow Minimal example - Part 2.html
HTML
204.8 B
4.1 TensorFlow_MNIST_with_comments_Part_2.html
HTML
204.8 B
5. Activation functions.mp4
MP4
8.7 MB
5. Activation functions.vtt
VTT
4.5 KB
5. An overview of RNNs.mp4
MP4
4.9 MB
5. An overview of RNNs.vtt
VTT
3.2 KB
5. Declaring the loss and the optimization algorithm.mp4
MP4
7.1 MB
5. Declaring the loss and the optimization algorithm.vtt
VTT
3.1 KB
5. Learning rate schedules. A picture.mp4
MP4
3.1 MB
5. Learning rate schedules. A picture.vtt
VTT
1.9 KB
5. Loss function and gradient descent - introducing optimizers.mp4
MP4
9.7 MB
5. Loss function and gradient descent - introducing optimizers.vtt
VTT
4.2 KB
5. Minimal example - Exercises.html
HTML
1.6 KB
5. N-fold cross validation.mp4
MP4
7 MB
5. N-fold cross validation.vtt
VTT
3.7 KB
5. One-hot and binary encoding.mp4
MP4
6.2 MB
5. One-hot and binary encoding.vtt
VTT
4.2 KB
5. Preprocessing exercise.html
HTML
409.6 B
5. Tensors.mp4
MP4
22.5 MB
5. Tensors.vtt
VTT
3.2 KB
5. The Jupyter dashboard - part 1.mp4
MP4
5.6 MB
5. The Jupyter dashboard - part 1.vtt
VTT
2.8 KB
5. Types of machine learning.mp4
MP4
12.2 MB
5. Types of machine learning.vtt
VTT
4.6 KB
5.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
5.1 Minimal_example_Exercise_2_Solution.html
HTML
102.4 B
5.1 Preprocessing exercise.html
HTML
102.4 B
5.1 TensorFlow Minimal example - Part 3.html
HTML
204.8 B
5.1 TensorFlow_MNIST_with_comments_Part_3.html
HTML
204.8 B
5.1 Tensors Notebook.html
HTML
102.4 B
5.10 Minimal_example_Exercise_6_Solution.html
HTML
102.4 B
5.2 Minimal_example_Exercise_3.d. Solution.html
HTML
204.8 B
5.3 Minimal_example_Exercise_4_Solution.html
HTML
102.4 B
5.4 Minimal_example_Exercise_3.b. Solution.html
HTML
204.8 B
5.5 Minimal_example_All_Exercises.html
HTML
102.4 B
5.6 Minimal_example_Exercise_1_Solution.html
HTML
102.4 B
5.7 Minimal_example_Exercise_3.c. Solution.html
HTML
204.8 B
5.8 Minimal_example_Exercise_5_Solution.html
HTML
102.4 B
5.9 Minimal_example_Exercise_3.a. Solution.html
HTML
204.8 B
6. Accuracy of prediction.mp4
MP4
12.4 MB
6. Accuracy of prediction.vtt
VTT
4.6 KB
6. Adaptive learning rate schedules.mp4
MP4
8.9 MB
6. Adaptive learning rate schedules.vtt
VTT
4.6 KB
6. Addition and Subtraction of Matrices.mp4
MP4
32.6 MB
6. Addition and Subtraction of Matrices.vtt
VTT
3.5 KB
6. An overview of non-NN approaches.mp4
MP4
7.8 MB
6. An overview of non-NN approaches.vtt
VTT
4.6 KB
6. Create a class for batching.mp4
MP4
27.6 MB
6. Create a class for batching.vtt
VTT
6.9 KB
6. Early stopping.mp4
MP4
9.4 MB
6. Early stopping.vtt
VTT
6 KB
6. Model output.mp4
MP4
14.3 MB
6. Model output.vtt
VTT
6.9 KB
6. Softmax activation.mp4
MP4
7.4 MB
6. Softmax activation.vtt
VTT
7.4 MB
6. The Jupyter dashboard - part 2.mp4
MP4
10.9 MB
6. The Jupyter dashboard - part 2.vtt
VTT
6 KB
6. Types of machine learning - Quiz.html
HTML
204.8 B
6.1 Addition and Subtraction Python Notebook.html
HTML
204.8 B
6.1 Class.html
HTML
102.4 B
6.1 TensorFlow - Minimal example complete.html
HTML
204.8 B
6.1 TensorFlow_MNIST_with_comments_Part_4.html
HTML
204.8 B
7. Adaptive moment estimation.mp4
MP4
7.8 MB
7. Adaptive moment estimation.vtt
VTT
2.9 KB
7. Backpropagation.mp4
MP4
11.1 MB
7. Backpropagation.vtt
VTT
6.5 MB
7. Batching and early stopping.mp4
MP4
4.6 MB
7. Batching and early stopping.vtt
VTT
2.5 KB
7. Errors when Adding Matrices.mp4
MP4
11.2 MB
7. Errors when Adding Matrices.vtt
VTT
2.3 KB
7. Jupyter Shortcuts.html
HTML
307.2 B
7. Minimal example - Exercises.html
HTML
1.6 KB
7. Outlining the model.mp4
MP4
19.5 MB
7. Outlining the model.vtt
VTT
6.1 KB
7. The linear model.mp4
MP4
9.1 MB
7. The linear model.vtt
VTT
3.5 KB
7.1 Course Notes - Section 2.pdf.pdf
PDF
927.7 KB
7.1 Errors when Adding Matrices Python Notebook.html
HTML
204.8 B
7.1 Outlining the model.html
HTML
102.4 B
7.1 Shortcuts for Jupyter.pdf.pdf
PDF
619.2 KB
7.1 TensorFlow_MNIST_with_comments_Part_5.html
HTML
204.8 B
7.1 TensorFlow_Minimal_Example_Exercise_1_Solution.html
HTML
204.8 B
7.2 TensorFlow_Minimal_Example_Exercise_2_3_Solution.html
HTML
204.8 B
7.3 TensorFlow_Minimal_Example_Exercise_2_1_Solution.html
HTML
204.8 B
7.4 TensorFlow_Minimal_Example_All_Exercises.html
HTML
204.8 B
7.5 TensorFlow_Minimal_Example_Exercise_3_Solution.html
HTML
204.8 B
7.6 TensorFlow_Minimal_Example_Exercise_2_2_Solution.html
HTML
204.8 B
7.7 TensorFlow_Minimal_Example_Exercise_4_Solution.html
HTML
204.8 B
7.8 TensorFlow_Minimal_Example_Exercise_2_4_Solution.html
HTML
204.8 B
8. Backpropagation - visual representation.mp4
MP4
6.8 MB
8. Backpropagation - visual representation.vtt
VTT
3.5 KB
8. Learning.mp4
MP4
15.9 MB
8. Learning.vtt
VTT
8.9 KB
8. Optimizing the algorithm.mp4
MP4
12.2 MB
8. Optimizing the algorithm.vtt
VTT
5.7 KB
8. The Jupyter dashboard - Quiz.html
HTML
204.8 B
8. The linear model - Quiz.html
HTML
204.8 B
8. Transpose of a Matrix.mp4
MP4
38.1 MB
8. Transpose of a Matrix.vtt
VTT
4.7 KB
8.1 Optimizing the algorithm.html
HTML
102.4 B
8.1 TensorFlow_MNIST_with_comments_Part_6.html
HTML
204.8 B
8.1 Transpose of a Matrix Python Notebook.html
HTML
204.8 B
9. Discuss the results and test.mp4
MP4
22 MB
9. Discuss the results and test.vtt
VTT
7.2 KB
9. Dot Product of Vectors.mp4
MP4
24 MB
9. Dot Product of Vectors.vtt
VTT
3.7 KB
9. Installing the TensorFlow package.mp4
MP4
4.9 MB
9. Installing the TensorFlow package.vtt
VTT
2.8 KB
9. Interpreting the result.mp4
MP4
5.4 MB
9. Interpreting the result.vtt
VTT
2.6 KB
9. Need Help with Linear Algebra.html
HTML
819.2 B
9.1 Dot Product Python Notebook.html
HTML
204.8 B
9.1 Interpreting the result.html
HTML
102.4 B
9.1 TensorFlow_MNIST_with_comments.html
HTML
102.4 B
[CourseClub.Me].url
URL
0 B
[DesireCourse.Net].url
URL
0 B

Description

Related Torrents

Location

Trackers

Tracker name
http://0d.kebhana.mx:443/announce
udp://bigfoot1942.sektori.org:6969/announce
https://tracker.fastdownload.xyz:443/announce
https://opentracker.xyz:443/announce
http://open.trackerlist.xyz:80/announce
udp://tracker.birkenwald.de:6969/announce
udp://tracker.vanitycore.co:6969/announce
http://torrent.nwps.ws:80/announce
udp://tracker.port443.xyz:6969/announce
udp://tracker.tiny-vps.com:6969/announce
http://t.nyaatracker.com:80/announce
udp://tracker.torrent.eu.org:451/announce
udp://retracker.lanta-net.ru:2710/announce
udp://retracker.hotplug.ru:2710/announce
udp://tracker.zer0day.to:1337/announce
udp://tracker.leechers-paradise.org:6969/announce
udp://coppersurfer.tk:6969/announce
Torrent hash: