Coursera - Generative Deep Learning with TensorFlow

426.57 MB | 00:06:40 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
01 welcome-to-course-4 (71.47 MB)
02 style-transfer-intro (6.83 MB)
05 style-transfer-conceptual-overview (8.03 MB)
07 pre-processing-inputs (4.29 MB)
08 extracting-style-and-content-features (9.51 MB)
10 total-loss-and-content-loss (6.23 MB)
11 style-loss (4.04 MB)
13 update-the-generated-image (3.42 MB)
14 optional-gram-matrix (5.6 MB)
15 optional-einstein-notation (8.05 MB)
16 optional-einsum-in-code (2.87 MB)
01 total-variation-loss (3.49 MB)
01 fast-neural-style-transfer (4.46 MB)
01 introduction (6.09 MB)
02 first-autoencoder (9.69 MB)
03 mnist-autoencoder (6.71 MB)
01 mnist-deep-autoencoder (6.09 MB)
02 convolutional-autoencoder (8.2 MB)
03 denoising-with-an-autoencoder (6.35 MB)
01 variational-autoencoders-overview (6.62 MB)
02 vae-architecture-and-code (5.16 MB)
03 sampling-layer-and-encoder (5.68 MB)
04 decoder (4.87 MB)
05 loss-function-and-model-definition (5.06 MB)
07 train-the-vae-model (3.92 MB)
01 introduction (6.24 MB)
03 first-gan-architecture (7.8 MB)
05 first-gan-training-loop (7.92 MB)
01 dcgans (6.56 MB)
03 face-generator (11.05 MB)
04 face-generator-discriminator (6.67 MB)
06 conclusions (21.73 MB)
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