Ai

Explore the theoretical foundations of reinforcement learning, from Markov Decision Processes and Bellman equations to Q-learning and deep reinforcement learning, with practical insights and minimal code examples.

Learn how to transform Victor Hugo's 1,400-page Les Misérables into structured, queryable data using Gemini 2.5 Flash and ontology-driven extraction. This comprehensive guide shows how to map complex relationships across massive documents with perfect context preservation, turning unstructured text into actionable business intelligence.

Learn how to build scalable async job processing systems with FastAPI, Redis, and Celery through a practical fraud detection use case that processes user clickstream data.

Learn how to use LM Studio CLI to download and run MLX-optimized models locally on Mac Apple Silicon, featuring Qwen2.5-Omni-3B for coding assistance and best practices for local AI development.