Alice's Adventures in a Differentiable Wonderland -- Volume I, A Tour of the Land
Simone Scardapane

Neural networks surround us, in the form of large language models, speech transcription systems, molecular discovery algorithms, robotics, and much more. Stripped of anything else, neural networks are compositions of differentiable primitives, and studying them means learning how to program and how to interact with these models, a particular example of what is called differentiable programming.
This primer is an introduction to this fascinating field imagined for someone, like Alice, who has just ventured into this strange differentiable wonderland. I overview the basics of optimizing a function via automatic differentiation, and a selection of the most common designs for handling sequences, graphs, texts, and audios. The focus is on a intuitive, self-contained introduction to the most important design techniques, including convolutional, attentional, and recurrent blocks, hoping to bridge the gap between theory and code (PyTorch and JAX) and leaving the reader capable of understanding some of the most advanced models out there, such as large language models (LLMs) and multimodal architectures. 

Lecture 1: Introduction to Reinforcement Learning

Lecture 2: Markov Decision Processes

Lecture 3: Planning by Dynamic Programming

Lecture 4: Model-Free Prediction

Lecture 5: Model-Free Control

Lecture 6: Value Function Approximation

Lecture 7: Policy Gradient Methods

Lecture 8: Integrating Learning and Planning

Lecture 9: Exploration and Exploitation

Lecture 10: Case Study: RL in Classic Games

A powerful document question-answering tool that connects to your local Ollama models. Create, manage, and interact with RAG systems for all your document needs.

This experiment lets you play a duet with the computer. Just play some notes, and the computer will respond to your melody. You don’t even have to know how to play piano—it’s fun to just press some keys and listen to what comes back. You can click the keyboard, use your computer keys, or even plug in a MIDI keyboard. It's just one example of how machine learning can inspire people to be creative in new ways.

A cognitive neural architecture able to learn and communicate through natural language

TensorFlow is an Open Source Software Library for Machine Intelligence, by Google

softs & data for nlp on french