d2l-ai/d2l-zh-pytorch-slides

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• chapter_preliminaries/ndarray.ipynb
• chapter_preliminaries/pandas.ipynb
• chapter_preliminaries/linear-algebra.ipynb
• chapter_preliminaries/calculus.ipynb
• chapter_preliminaries/autograd.ipynb
• chapter_preliminaries/lookup-api.ipynb
• chapter_linear-networks/linear-regression.ipynb
• chapter_linear-networks/linear-regression-scratch.ipynb
• chapter_linear-networks/linear-regression-concise.ipynb
• chapter_linear-networks/image-classification-dataset.ipynb
• chapter_linear-networks/softmax-regression-scratch.ipynb
• chapter_linear-networks/softmax-regression-concise.ipynb
• chapter_multilayer-perceptrons/mlp.ipynb
• chapter_multilayer-perceptrons/mlp-scratch.ipynb
• chapter_multilayer-perceptrons/mlp-concise.ipynb
• chapter_multilayer-perceptrons/underfit-overfit.ipynb
• chapter_multilayer-perceptrons/weight-decay.ipynb
• chapter_multilayer-perceptrons/dropout.ipynb
• chapter_multilayer-perceptrons/numerical-stability-and-init.ipynb
• chapter_multilayer-perceptrons/kaggle-house-price.ipynb
• chapter_deep-learning-computation/model-construction.ipynb
• chapter_deep-learning-computation/parameters.ipynb
• chapter_deep-learning-computation/custom-layer.ipynb
• chapter_deep-learning-computation/read-write.ipynb
• chapter_deep-learning-computation/use-gpu.ipynb
• chapter_convolutional-neural-networks/conv-layer.ipynb
• chapter_convolutional-neural-networks/padding-and-strides.ipynb
• chapter_convolutional-neural-networks/channels.ipynb
• chapter_convolutional-neural-networks/pooling.ipynb
• chapter_convolutional-neural-networks/lenet.ipynb
• chapter_convolutional-modern/alexnet.ipynb
• chapter_convolutional-modern/vgg.ipynb
• chapter_convolutional-modern/nin.ipynb
• chapter_convolutional-modern/googlenet.ipynb
• chapter_convolutional-modern/batch-norm.ipynb
• chapter_convolutional-modern/resnet.ipynb
• chapter_convolutional-modern/densenet.ipynb
• chapter_recurrent-neural-networks/sequence.ipynb
• chapter_recurrent-neural-networks/text-preprocessing.ipynb
• chapter_recurrent-neural-networks/language-models-and-dataset.ipynb
• chapter_recurrent-neural-networks/rnn-scratch.ipynb
• chapter_recurrent-neural-networks/rnn-concise.ipynb
• chapter_recurrent-modern/gru.ipynb
• chapter_recurrent-modern/lstm.ipynb
• chapter_recurrent-modern/deep-rnn.ipynb
• chapter_recurrent-modern/bi-rnn.ipynb
• chapter_recurrent-modern/machine-translation-and-dataset.ipynb
• chapter_recurrent-modern/encoder-decoder.ipynb
• chapter_recurrent-modern/seq2seq.ipynb
• chapter_attention-mechanisms/nadaraya-waston.ipynb
• chapter_attention-mechanisms/attention-scoring-functions.ipynb
• chapter_attention-mechanisms/bahdanau-attention.ipynb
• chapter_attention-mechanisms/multihead-attention.ipynb
• chapter_attention-mechanisms/self-attention-and-positional-encoding.ipynb
• chapter_attention-mechanisms/transformer.ipynb
• chapter_computational-performance/multiple-gpus.ipynb
• chapter_computational-performance/multiple-gpus-concise.ipynb
• chapter_computer-vision/image-augmentation.ipynb
• chapter_computer-vision/fine-tuning.ipynb
• chapter_computer-vision/bounding-box.ipynb
• chapter_computer-vision/anchor.ipynb
• chapter_computer-vision/multiscale-object-detection.ipynb
• chapter_computer-vision/object-detection-dataset.ipynb
• chapter_computer-vision/ssd.ipynb
• chapter_computer-vision/semantic-segmentation-and-dataset.ipynb
• chapter_computer-vision/transposed-conv.ipynb
• chapter_computer-vision/fcn.ipynb
• chapter_computer-vision/neural-style.ipynb
• chapter_computer-vision/kaggle-cifar10.ipynb
• chapter_computer-vision/kaggle-dog.ipynb
• chapter_natural-language-processing-applications/natural-language-inference-and-dataset.ipynb
• chapter_natural-language-processing-applications/natural-language-inference-bert.ipynb