📖 Dive into Deep Learning — a free interactive textbook on deep learning (surprise!), used by many universities worldwide.

Why this is a must-have to bookmark (and preferably open occasionally):

1️⃣ Interactivity. The entire book is essentially a huge set of Jupyter notebooks. Many mathematical concepts and practical examples are immediately backed by reproducible code.

2️⃣ Framework-agnostic. The authors went the extra mile and wrote examples for PyTorch, JAX, and TensorFlow (and MXNet, rest in peace). This, by the way, is the best way to quickly switch from one tool to another by comparing implementations side by side.

3️⃣ Breadth and depth. From basic linear regression written from scratch to transformers, RL, Gaussian processes, and recommendation systems.

This is not light bedtime reading. To digest the material, you'll have to strain your brain, recall linear algebra, derivatives, and not cry at the sight of mathematical notation.

The book itself is here 📖
The code repository is here 🧑‍💻

#левел_ап