You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

Synthetic data consists of artificially generated data. When data are scarce, or of poor
quality, synthetic data can be used, for example, to improve the performance of machine …

The apparent contradiction in the title is a wordplay on the different meanings attributed to
the word reproducible across different scientific fields. What we imply is that unreproducible …

This practical guide provides nearly 200 self-contained recipes to help you solve machine
learning challenges you may encounter in your daily work. If you're comfortable with Python …

This open-source book represents our attempt to make deep learning approachable,
teaching readers the concepts, the context, and the code. The entire book is drafted in …

Deep learning's successes are often attributed to its ability to automatically discover new
representations of the data, rather than relying on handcrafted features like other learning …

Machine-learning algorithms have become deeply embedded in contemporary society. As
such, ample attention has been paid to the contents, biases, and underlying assumptions of …

Machine learning heavily relies on data, but real-world applications often encounter various
data-related issues. These include data of poor quality, insufficient data points leading to …

This book offers a comprehensive introduction to the central ideas that underpin deep
learning. It is intended both for newcomers to machine learning and for those already …

Understanding deep learning is also a job for physicists | Nature Physics Skip to main content
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