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dlc-video-1-6-tensor-internals
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Wednesday, 24 February 2021
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dlc-video-8-1-CV-tasks
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dlc-video-8-2-image-classification
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dlc-video-8-3-object-detection
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dlc-video-8-4-segmentation
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dlc-video-9-1-looking-at-parameters
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dlc-video-9-2-looking-at-activations
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dlc-video-9-3-visualizing-in-input
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dlc-video-11-3-conditional-GAN
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dlc-video-11-4-persistence
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dlc-video-12-1-RNN-basics
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dlc-video-12-2-LSTM-and-GRU
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dlc-video-12-3-word-embeddings-and-translation
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dlc-video-13-1-attention-memory-translation
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dlc-video-13-2-attention-mechanisms
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dlc-video-13-3-transformers
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dlc-video-4-1-DAG-networks
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dlc-video-4-2-autograd
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dlc-video-4-3-modules-and-batch-processing
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dlc-video-4-4-convolutions
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dlc-video-4-5-pooling
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dlc-video-5-1-cross-entropy-loss
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dlc-video-5-2-SGD
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dlc-video-5-3-optim
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dlc-video-5-4-l2-l1-penalties
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dlc-video-5-5-initialization
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dlc-video-5-6-architecture-and-training
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dlc-video-5-7-writing-an-autograd-function
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dlc-video-6-1-benefits-of-depth
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dlc-video-6-2-rectifiers
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dlc-video-6-3-dropout
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dlc-video-6-4-batch-normalization
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dlc-video-6-5-residual-networks
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dlc-video-6-6-using-GPUs
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dlc-video-7-1-transposed-convolutions
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dlc-video-7-2-autoencoders
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dlc-video-1-1-from-anns-to-deep-learning
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dlc-video-1-2-current-success
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dlc-video-1-3-what-is-happening
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dlc-video-1-4-tensors-and-linear-regression
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Wednesday 24 February 2021
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dlc-video-1-5-high-dimension-tensors
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Wednesday 24 February 2021
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dlc-video-1-6-tensor-internals
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Wednesday 24 February 2021
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dlc-video-2-1-loss-and-risk
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Wednesday 24 February 2021
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dlc-video-2-2-overfitting
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dlc-video-2-3-bias-variance-dilemma
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dlc-video-2-4-evaluation-protocols
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Wednesday 24 February 2021
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dlc-video-2-5-basic-embeddings
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Wednesday 24 February 2021
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dlc-video-3-1-perceptron
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dlc-video-3-2-LDA
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dlc-video-3-3-features
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dlc-video-3-4-MLP
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dlc-video-3-5-gradient-descent
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