Mastering AI Engineering with Large Language Models: From Scratch to Production with PyTorch, RAG, and Reinforcement Learning
Mastering AI Engineering with Large Language Models: From Scratch to Production with PyTorch, RAG, and Reinforcement Learning
English | 2025 | ASIN: B0DY5CZ37Z | 93 pages | Epub | 1.35 MB
English | 2025 | ASIN: B0DY5CZ37Z | 93 pages | Epub | 1.35 MB
Build Intelligent Systems with LLMs, PyTorch, RAG, and Reinforcement Learning
Mastering AI Engineering with Large Language Models is a complete, hands-on guide for developers, engineers, and AI enthusiasts ready to design, build, and deploy cutting-edge AI solutions — from scratch to production.
Learn how to implement modern AI systems using PyTorch, train Large Language Models like DeepSeek 7B, apply Reinforcement Learning for intelligent agents, and combine LLMs with Retrieval-Augmented Generation (RAG) to build AI that responds in real time.
Inside the book:
Step-by-step tutorials on building neural networks using PyTorch
Train and fine-tune LLMs for text generation, chatbots, and code generation
Hands-on projects with Deep Q-Learning, Actor-Critic methods, and RL environments
Implement RAG pipelines using FAISS and LangChain for knowledge-augmented AI
Explore AI applications in automation, business, search engines, and healthcare
Whether you're a beginner aiming to understand the AI development lifecycle or a professional seeking to enhance your ML stack, this book delivers a practical roadmap with production-grade examples.