d2l-ai/d2l-pytorch-slides
This repo contains generated notebook slides. To open it locally, we suggest you to install the rise extension.
You can also preview them in nbviwer:
- 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-regression/linear-regression.ipynb
- chapter_linear-regression/synthetic-regression-data.ipynb
- chapter_linear-regression/linear-regression-scratch.ipynb
- chapter_linear-regression/linear-regression-concise.ipynb
- chapter_linear-regression/weight-decay.ipynb
- chapter_linear-classification/image-classification-dataset.ipynb
- chapter_linear-classification/classification.ipynb
- chapter_linear-classification/softmax-regression-scratch.ipynb
- chapter_linear-classification/softmax-regression-concise.ipynb
- chapter_multilayer-perceptrons/mlp.ipynb
- chapter_multilayer-perceptrons/mlp-implementation.ipynb
- chapter_multilayer-perceptrons/numerical-stability-and-init.ipynb
- chapter_multilayer-perceptrons/dropout.ipynb
- chapter_multilayer-perceptrons/kaggle-house-price.ipynb
- chapter_builders-guide/model-construction.ipynb
- chapter_builders-guide/parameters.ipynb
- chapter_builders-guide/init-param.ipynb
- chapter_builders-guide/custom-layer.ipynb
- chapter_builders-guide/read-write.ipynb
- chapter_builders-guide/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-sequence.ipynb
- chapter_recurrent-neural-networks/language-model.ipynb
- chapter_recurrent-neural-networks/rnn-scratch.ipynb
- chapter_recurrent-neural-networks/rnn-concise.ipynb
- chapter_recurrent-modern/lstm.ipynb
- chapter_recurrent-modern/gru.ipynb
- chapter_recurrent-modern/deep-rnn.ipynb
- chapter_recurrent-modern/machine-translation-and-dataset.ipynb
- chapter_recurrent-modern/encoder-decoder.ipynb
- chapter_recurrent-modern/seq2seq.ipynb
- chapter_attention-mechanisms-and-transformers/attention-pooling.ipynb
- chapter_attention-mechanisms-and-transformers/attention-scoring-functions.ipynb
- chapter_attention-mechanisms-and-transformers/bahdanau-attention.ipynb
- chapter_attention-mechanisms-and-transformers/multihead-attention.ipynb
- chapter_attention-mechanisms-and-transformers/self-attention-and-positional-encoding.ipynb
- chapter_attention-mechanisms-and-transformers/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-pretraining/bert.ipynb
- chapter_natural-language-processing-pretraining/bert-dataset.ipynb
- chapter_natural-language-processing-pretraining/bert-pretraining.ipynb
- chapter_natural-language-processing-applications/natural-language-inference-and-dataset.ipynb
- chapter_natural-language-processing-applications/natural-language-inference-bert.ipynb