The Little Book of Deep Learning
Book Details
| Author | François Fleuret |
| Publisher | University of Geneva |
| Published | 2024 |
| Edition | 1st |
| Paperback | 185 pages |
| Language | English |
| License | Creative Commons Attribution-NonCommercial-ShareAlike |
Book Description
The current period of progress in artificial intelligence was triggered when Krizhevsky et al. demonstrated that an artificial neural network designed twenty years earlier could outperform complex state-of-the-art image recognition methods by a huge margin, simply by being a hundred times larger and trained on a dataset similarly scaled up.
This breakthrough was made possible thanks to GPUs, highly parallel consumer-grade computing devices developed for real-time image synthesis and repurposed for artificial neural networks.
Since then, under the umbrella term of "deep learning," innovations in the structures of these networks, the strategies to train them, and dedicated hardware have allowed for an exponential increase in both their size and the quantity of training data they take advantage of. This has resulted in a wave of successful applications across technical domains, from computer vision and robotics to speech processing, and since 2020 in the development of Large Language Models with general protoreasoning capabilities.
Although the bulk of deep learning is not difficult to understand, it combines diverse components such as linear algebra, calculus, probabilities, optimization, signal processing, programming, algorithmics, and high-performance computing, making it complicated to learn.
Instead of trying to be exhaustive, this little book is limited to the background necessary to understand a few important models. This open book is a short introduction to deep learning for readers with a STEM background. It aims at providing the necessary background to understand landmark AI models for image generation and language understanding.
This book is available under a Creative Commons Attribution-NonCommercial-ShareAlike license (CC BY-NC-SA), which means that you are free to copy, distribute, and modify it, as long as you credit the original author, don't use it for commercial purposes, and share any adaptations under the same license.
If you enjoyed the book and would like to support the author, you can purchase a printed copy (hardcover or paperback) from official retailers.
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