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chapter_appendix-mathematics-for-deep-learning

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chapter_appendix-tools-for-deep-learning

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chapter_attention-mechanisms-and-transformers

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chapter_builders-guide

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chapter_computational-performance

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chapter_computer-vision

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chapter_convolutional-modern

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chapter_convolutional-neural-networks

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chapter_gaussian-processes

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chapter_generative-adversarial-networks

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chapter_hyperparameter-optimization

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chapter_installation

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chapter_introduction

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chapter_linear-classification

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chapter_linear-regression

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chapter_multilayer-perceptrons

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chapter_natural-language-processing-applications

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chapter_natural-language-processing-pretraining

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chapter_notation

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chapter_optimization

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chapter_preface

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chapter_preliminaries

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chapter_recommender-systems

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chapter_recurrent-modern

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chapter_recurrent-neural-networks

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chapter_references

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chapter_reinforcement-learning

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static/latex_style

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.gitignore

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d2l.bib

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index.ipynb

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LICENSE.txt

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README.md

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setup.py

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README.md

D2L PyTorch Notebooks

Jupyter notebooks for Dive into Deep Learning implemented with PyTorch.