Coursera - Custom Models, Layers, and Loss Functions with TensorFlow

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397.31 MB | 00:06:03 | mp4 | 1280X720  | 16:9
Genre:eLearning |Language:English

Files Included :
01 a-conversation-with-andrew-ng-overview-of-the-specialization  (41.08 MB)
02 a-conversation-with-andrew-ng-overview-of-course-1  (29.34 MB)
01 welcome-to-the-course  (2.57 MB)
02 introduction-to-the-functional-apis  (13.81 MB)
01 declaring-and-stacking-layers  (8.73 MB)
02 branching-models  (9.06 MB)
01 creating-a-multi-output-model  (9.08 MB)
03 multi-output-code-walkthrough  (18.22 MB)
01 siamese-network-a-multiple-input-model  (6.53 MB)
03 coding-a-multi-input-siamese-network  (6.06 MB)
05 siamese-network-code-walkthrough  (25.02 MB)
01 welcome-to-week-2  (6.25 MB)
02 creating-a-custom-loss-function  (4.64 MB)
04 coding-the-huber-loss-function  (3.52 MB)
05 huber-loss-code-walkthrough  (4.08 MB)
01 adding-hyperparameters-to-custom-loss-functions  (8.41 MB)
02 turning-loss-functions-into-classes  (4.63 MB)
03 huber-object-loss-code-walkthrough  (7.46 MB)
01 contrastive-loss  (6.31 MB)
03 coding-contrastive-loss  (3.15 MB)
01 intro-custom-layers  (5.9 MB)
02 introduction-to-lambda-layers  (6.58 MB)
03 custom-functions-from-lambda-layers  (5.98 MB)
04 exploring-custom-relu-with-lambda-layers  (10.71 MB)
01 architecture-of-a-custom-layer  (4.54 MB)
02 coding-your-own-custom-dense-layer  (8.89 MB)
03 training-a-neural-network-with-your-custom-layer  (5.2 MB)
04 custom-layer-code-walkthrough  (11.2 MB)
01 activating-your-custom-layer  (10 MB)
02 custom-layer-with-activation-code-walkthrough  (9.92 MB)
01 intro-to-custom-models  (6.52 MB)
02 complex-architectures-with-the-functional-api  (5.83 MB)
03 coding-a-wide-and-deep-model  (5.38 MB)
01 using-the-model-class-to-simplify-architectures  (8.16 MB)
02 understanding-residual-networks  (9.75 MB)
01 coding-a-residual-network-with-the-model-class  (11.03 MB)
02 resnet-code-walkthrough  (12.36 MB)
01 built-in-callbacks  (10.37 MB)
01 custom-callbacks  (13.62 MB)
02 custom-callbacks-code-walkthrough  (12.06 MB)

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