Udemy Mastering Neural Style Transfer Tensorflow Keras and Python
Seeders : 7 Leechers : 2
| Torrent Hash : | 498A5690A9C8A370CA952F3FBE62BB15C7A20982 |
| Torrent Added : | at July 27, 2023, 10:02 a.m. in Other |
| Torrent Size : | 373.8 MB |
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Udemy Mastering Neural Style Transfer Tensorflow Keras and Python
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Udemy Mastering Neural Style Transfer Tensorflow Keras and Python
Get Bonus Downloads Here.url -
1 - Introduction.mp4 -
2 - What is Neural Style Transfer.mp4 -
3 - About this Project.mp4 -
4 - Why Should we Learn.mp4 -
5 - Applications.mp4 -
6 - Why Keras and Python.mp4 -
7 - Why Google Colab.mp4 -
10 - Activate GPU.mp4 -
11 - Checking the availability and usage of GPUs.mp4 -
12 - Mount Google Drive to Google Colab.mp4 -
13 - Necessary library imports.mp4 -
14 - Setting the directory path.mp4 -
15 - Displaying the base image and the style reference.mp4 -
16 - Defining the desired dimensions.mp4 -
17 - Preprocesses an image.mp4 -
18 - Convert the generated image back to its original format.mp4 -
19 - Calculate the Gram matrix.mp4 -
20 - Calculates the style loss.mp4 -
21 - Calculates the content loss.mp4 -
22 - Calculates the total variation loss.mp4 -
23 - Loading the VGG19.mp4 -
24 - Creating a dictionary.mp4 -
25 - Building a feature extraction model.mp4 -
26 - Define the names of the style layers and the content layer.mp4 -
27 - Set the weights.mp4 -
28 - Calculates the total loss.mp4 -
29 - Computes the loss and gradients.mp4 -
30 - Set up the optimizer.mp4 -
31 - Preprocess the base image style reference image and combination image.mp4 -
32 - Perform the style transfer optimization loop.mp4 -
33 - Save and display the final generated image.mp4 -
8 - Setup the Working Directory.mp4 -
8 - code.ipynb -
8 - content-image.jpg -
8 - style-image.jpg -
9 - Contents in Directory.mp4 -
Bonus Resources.txt -
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182 bytes
1 - Introduction.mp4 -
20.1 MB
2 - What is Neural Style Transfer.mp4 -
20.4 MB
3 - About this Project.mp4 -
15.1 MB
4 - Why Should we Learn.mp4 -
36.0 MB
5 - Applications.mp4 -
44.6 MB
6 - Why Keras and Python.mp4 -
7.8 MB
7 - Why Google Colab.mp4 -
6.0 MB
10 - Activate GPU.mp4 -
8.3 MB
11 - Checking the availability and usage of GPUs.mp4 -
11.4 MB
12 - Mount Google Drive to Google Colab.mp4 -
5.6 MB
13 - Necessary library imports.mp4 -
8.8 MB
14 - Setting the directory path.mp4 -
11.2 MB
15 - Displaying the base image and the style reference.mp4 -
6.7 MB
16 - Defining the desired dimensions.mp4 -
5.6 MB
17 - Preprocesses an image.mp4 -
9.0 MB
18 - Convert the generated image back to its original format.mp4 -
9.7 MB
19 - Calculate the Gram matrix.mp4 -
8.6 MB
20 - Calculates the style loss.mp4 -
7.6 MB
21 - Calculates the content loss.mp4 -
3.7 MB
22 - Calculates the total variation loss.mp4 -
5.5 MB
23 - Loading the VGG19.mp4 -
6.5 MB
24 - Creating a dictionary.mp4 -
4.2 MB
25 - Building a feature extraction model.mp4 -
6.0 MB
26 - Define the names of the style layers and the content layer.mp4 -
6.6 MB
27 - Set the weights.mp4 -
4.7 MB
28 - Calculates the total loss.mp4 -
25.3 MB
29 - Computes the loss and gradients.mp4 -
7.1 MB
30 - Set up the optimizer.mp4 -
5.3 MB
31 - Preprocess the base image style reference image and combination image.mp4 -
9.4 MB
32 - Perform the style transfer optimization loop.mp4 -
12.8 MB
33 - Save and display the final generated image.mp4 -
10.4 MB
8 - Setup the Working Directory.mp4 -
8.7 MB
8 - code.ipynb -
616.1 KB
8 - content-image.jpg -
170.6 KB
8 - style-image.jpg -
43.3 KB
9 - Contents in Directory.mp4 -
14.2 MB
Bonus Resources.txt -
386 bytes
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