Building AI Systems with Python: Practical Machine Learning and Agentic Workflows with Python and PyTorch

This book is a practical, end-to-end guide for engineers and practitioners who want to move beyond prototypes and confidently deploy machine learning and large language model solutions in real-world environments. This book guides through the entire modern machine learning lifecycle.You’ll start with foundations using NumPy, Pandas, and PyArrow for data pipelines, then build solid baselines with scikit-learn.From there, you advance into deep learning with PyTorch, transformers, and LLM adaptation techniques such as LoRA and QLoRA.You’ll explore diffusion and multimodal models, and learn to build retrieval-augmented generation systems with FAISS and pgvector.Practical chapters cover agents, tool use, evaluation frameworks, observability, and responsible AI practices including privacy, safety, and governance.Finally, you’ll master deployment techniques using FastAPI, Ray Serve, TorchServe, and cutting-edge LLM serving engines like vLLM and TGI.Each concept is paired with clear code exampl