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11x001 2021Deep learning course

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Zoom fin 6.2, 6.3

Zoom 6.1, début 6.2

Zoom fin 5.3, 5.4

Zoom 5.2, début 5.3

Zoom fin 4.2, 5.1

Zoom 3.3, début 3.4

Zoom fin 3.1, 3.2

Zoom fin 2.4, début 3.1

Zoom fin 2.2, 2.3, début 2.4

Zoom fin 1.4, 2.1 et début 2.2

Zoom fin 1.3 et début 1.4 (partiel, problème technique)

Zoom 1.1 et 1.2

Dlc-video-3-5-gradient-descent

Dlc-video-3-6-backprop

Dlc-video-3-1-perceptron

Dlc-video-3-2-LDA

Dlc-video-3-3-features

Dlc-video-3-4-MLP

Dlc-video-1-1-from-anns-to-deep-learning

Dlc-video-1-2-current-success

Dlc-video-1-3-what-is-happening

Dlc-video-1-4-tensors-and-linear-regression

Dlc-video-1-5-high-dimension-tensors

Dlc-video-1-6-tensor-internals

Dlc-video-2-1-loss-and-risk

Dlc-video-2-2-overfitting

Dlc-video-2-3-bias-variance-dilemma

Dlc-video-2-4-evaluation-protocols

Dlc-video-2-5-basic-embeddings

Dlc-video-4-1-DAG-networks

Dlc-video-4-2-autograd

Dlc-video-4-3-modules-and-batch-processing

Dlc-video-4-4-convolutions

Dlc-video-4-5-pooling

Dlc-video-4-6-writing-a-module

Dlc-video-5-1-cross-entropy-loss

Dlc-video-5-2-SGD

Dlc-video-5-3-optim

Dlc-video-5-4-l2-l1-penalties

Dlc-video-5-5-initialization

Dlc-video-5-6-architecture-and-training

Dlc-video-5-7-writing-an-autograd-function

Dlc-video-6-1-benefits-of-depth

Dlc-video-6-2-rectifiers

Dlc-video-6-3-dropout

Dlc-video-6-4-batch-normalization

Dlc-video-6-5-residual-networks

Dlc-video-6-6-using-GPUs

Dlc-video-7-1-transposed-convolutions

Dlc-video-7-2-autoencoders

Dlc-video-7-3-denoising-autoencoders

Dlc-video-7-4-VAE

Dlc-video-8-1-CV-tasks

Dlc-video-8-2-image-classification

Dlc-video-8-3-object-detection

Dlc-video-8-4-segmentation

Dlc-video-8-5-dataloader-and-surgery

Dlc-video-9-1-looking-at-parameters

Dlc-video-9-2-looking-at-activations

Dlc-video-9-3-visualizing-in-input

Dlc-video-9-4-optimizing-inputs

Dlc-video-10-1-autoregression

Dlc-video-10-2-causal-convolutions

Dlc-video-10-3-NVP

Dlc-video-11-1-GAN

Dlc-video-11-2-Wasserstein-GAN

Dlc-video-11-3-conditional-GAN

Dlc-video-11-4-persistence

Dlc-video-12-1-RNN-basics

Dlc-video-12-2-LSTM-and-GRU

Dlc-video-12-3-word-embeddings-and-translation

Dlc-video-13-1-attention-memory-translation

Dlc-video-13-2-attention-mechanisms

Dlc-video-13-3-transformers