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Deep Learning with TensorFlow and Keras - 3rd Edition : Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models. by Kapoor, Amita

Table of Contents: “…Context autoencoder -- Colorization -- Innate relationship prediction -- Relative position -- Solving jigsaw puzzles -- Rotation -- Hybrid self-prediction -- VQ-VAE -- Jukebox -- DALL-E -- VQ-GAN -- Contrastive learning -- Training objectives -- Contrastive loss -- Triplet loss -- N-pair loss -- Lifted structural loss -- NCE loss -- InfoNCE loss -- Soft nearest neighbors loss -- Instance transformation -- SimCLR -- Barlow Twins -- BYOL -- Feature clustering -- DeepCluster -- SwAV -- InterCLR -- Multiview coding -- AMDIM -- CMC -- Multimodal models -- CLIP -- CodeSearchNet -- Data2Vec -- Pretext tasks -- Summary -- References -- Chapter 11: Reinforcement Learning -- An introduction to RL -- RL lingo -- Deep reinforcement learning algorithms -- How does the agent choose its actions, especially when untrained? …”
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