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Stanford CS229, MIT 6.S191, la série de Karpathy sur les réseaux de neurones, et plus encore. Des cours de machine learning gratuits sur YouTube qui valent vraiment votre temps.

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Glossaire IA 20 termes d'IA expliqués simplement — des réseaux de neurones au RAG →

Derniers guides IA et machine learning

AI Fundamentals

What Is a Recurrent Neural Network (RNN)? How Sequence Models Work

Learn what a recurrent neural network is, how RNNs process sequential data, and why transformers have largely replaced them in modern AI systems.
AI Fundamentals

What Is Unsupervised Learning? Definition, Techniques, and Real-World Uses

Learn what unsupervised learning is, how it finds patterns in unlabeled data, and why it powers clustering, anomaly detection, and more in 2026.
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What Is Multimodal AI? Definition, How It Works, and Why It Matters

Learn what multimodal AI is, how models process text, images, audio, and video together, and why multimodal AI is the frontier in 2026.
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What Is AI Alignment? Challenges & Why It Matters

Learn what AI alignment is, why ensuring AI systems act according to human values is difficult, and the key approaches in 2026.
AI Fundamentals

What Is Supervised Learning? Definition, How It Works, and Common Examples

Learn what supervised learning is, how models train on labeled data, and why it remains the most widely used machine learning approach.
AI Fundamentals

What Is a Diffusion Model? Definition, How It Generates Images, and Key Examples

Learn what a diffusion model is, how it generates images by reversing noise, and why diffusion models power Midjourney, DALL-E, and Stable Diffusion.
AI Fundamentals

What Is Fine-Tuning? Definition, Methods, and When to Use It

Learn what fine-tuning is in AI, how it adapts pre-trained models to specific tasks, and when fine-tuning is the right approach in 2026.
AI Fundamentals

What Is Transfer Learning? Definition, How It Works, and Why It Matters

Learn what transfer learning is, how it lets AI models reuse knowledge across tasks, and why it made modern AI development practical.
AI Fundamentals

What Is a Foundation Model? Definition, Examples, and Why They Dominate AI

Learn what a foundation model is, how these large pre-trained models work, and why they are the base layer of AI products in 2026.
AI Fundamentals

What Is Computer Vision? Definition, Techniques, and Real-World Applications

Learn what computer vision is, how machines interpret images and video, and the key applications driving the field in 2026.
AI Fundamentals

What Is an AI Agent? How They Work (2026)

Learn what an AI agent is, how autonomous agents plan and execute tasks, and why AI agents are a major trend in 2026.
AI Fundamentals

What Is Prompt Engineering? Techniques & Tips 2026

Learn what prompt engineering is, the core techniques for getting better AI outputs, and why it matters for using LLMs effectively.
AI Fundamentals

What Is Reinforcement Learning? Definition & Examples

Learn what reinforcement learning is, how agents learn through trial and error, and why RL powers game AI, robotics, and LLM alignment.
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What Is a Transformer (AI)? Definition, Architecture, and Why It Changed AI

Learn what a transformer is in AI, how the self-attention mechanism works, and why transformers power GPT, Claude, and modern AI.
AI Fundamentals

What Is RAG? Retrieval-Augmented Generation (2026)

Learn what retrieval-augmented generation (RAG) is, how it grounds LLM responses in real data, and why enterprises rely on RAG in 2026.
AI Fundamentals

What Is a Large Language Model? LLM Guide 2026

Learn what a large language model (LLM) is, how it generates text, and why models like GPT-4 and Claude matter in 2026.
AI Fundamentals

What Is Natural Language Processing (NLP)? Definition, Techniques, and Applications

Learn what natural language processing (NLP) is, the key techniques behind it, and how NLP powers search, chatbots, and translation.
AI Fundamentals

What Is a Neural Network? Definition, Architecture, and How It Learns

Understand what a neural network is, how its layers process data, and why neural networks are the building blocks of modern AI.
AI Fundamentals

What Is Machine Learning? Definition & Types (2026)

Clear, jargon-free explanation of machine learning -- what it is, how it works, the main types, and why it matters in 2026.
AI Fundamentals

What Is Deep Learning? Definition & How It Works 2026

A straightforward explanation of what deep learning is, how neural networks learn from data, and why deep learning drives modern AI.