📘 Chapters Overview

Welcome to the Julia implementation of Dive into Deep Learning (D2L.ai), a hands-on guide to deep learning that combines theory with practical coding examples. This project aims to reimagine the classic book using the power and simplicity of the Julia language and its machine learning ecosystem.

This page provides a high-level overview of each chapter and serves as an index to navigate the contents.

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Chapter Index

1. Linear Neural Networks for Regression

2. Linear Neural Networks for Classification

3. Multilayer Perceptrons

4. Convolution for Images

5. Modern Convolutional Neural Networks

6. Recurrent Neural Networks

7. Modern Recurrent Neural Networks

8. Attention Mechanisms and Transformers

9. Computer Vision