{"product_id":"practical-ai-engineering-a-hands-on-guide-to-building-scalable-ai-with-python-llms-rag-tensorflow-pytorch-and-kubernetes-from-scratch-to-master-9798294142926","title":"Practical AI Engineering: A Hands-on Guide to Building Scalable AI with Python, LLMs, RAG, TensorFlow, PyTorch and Kubernetes - From Scratch to Master","description":"\u003cp\u003e • Author(s): Juno Darian\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Machine Theory\u003c\/p\u003e\u003cp\u003e\u003cb\u003eBuild, Deploy, and Scale Real-World AI Systems-From Foundation Models to Full-Stack Production Pipelines\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eAre you ready to move beyond tutorials and toy models into the real world of scalable, production-ready AI? \u003cp\u003e\u003c\/p\u003e\u003ci\u003ePractical AI Engineering \u003c\/i\u003eis your complete, no-fluff, \u003cb\u003ehands-on guide to building modern AI applications from scratch to mastery. \u003c\/b\u003eWhether you're aiming to become a full-stack AI engineer, deploy cutting-edge LLMs (Large Language Models), or bring real-time Retrieval-Augmented Generation (RAG) systems into production, this book takes you there-step by step. \u003cp\u003e\u003c\/p\u003eWritten for engineers, ML practitioners, and developers who want more than just theoretical knowledge, this book equips you with \u003cb\u003ebattle-tested workflows, system design patterns, and toolchains \u003c\/b\u003eused by top AI teams. \u003cp\u003e\u003c\/p\u003e\u003cb\u003eWhat You'll Master Inside This Book: \u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e\u003cb\u003eAI Engineering from the Ground Up\u003c\/b\u003e\u003cbr\u003e- Learn what AI engineering really means: beyond models, into systems\u003cbr\u003e- Master the end-to-end AI lifecycle (Design → Deploy → Maintain)\u003cbr\u003e- Think like a systems engineer for real-world impact \u003cp\u003e\u003c\/p\u003e\u003cb\u003eThe Full Toolkit for Modern AI Engineers\u003c\/b\u003e\u003cbr\u003e- Python patterns, TensorFlow vs. PyTorch, FastAPI, HuggingFace, LangChain\u003cbr\u003e- Data pipelines, Docker, Kubernetes, and GitOps workflows\u003cbr\u003e- Experiment tracking, versioning, and CI\/CD automation \u003cp\u003e\u003c\/p\u003e\u003cb\u003eLLMs, Transformers, and Prompt Engineering in Practice\u003c\/b\u003e\u003cbr\u003e- Understand how GPT models work and scale\u003cbr\u003e- Use OpenAI APIs and HuggingFace models efficiently\u003cbr\u003e- Apply few-shot, chain-of-thought, and retrieval-augmented strategies\u003cbr\u003e- Implement LLMOps for inference, caching, and cost control \u003cp\u003e\u003c\/p\u003e\u003cb\u003eRetrieval-Augmented Generation (RAG) and GraphRAG\u003c\/b\u003e\u003cbr\u003e- Chunking, embeddings, and vector databases (FAISS, Pinecone, Qdrant)\u003cbr\u003e- Build RAG systems with LangChain, FastAPI, and custom memory\u003cbr\u003e- Go beyond text: create knowledge-augmented LLMs with Neo4j and GraphRAG\u003cbr\u003e- Complete projects: Legal QA bots, research assistants, scalable chatbots \u003cp\u003e\u003c\/p\u003e\u003cb\u003eAgentic AI and Multi-Tool Orchestration\u003c\/b\u003e\u003cbr\u003e- Build agents that use tools like Web Browsing, SQL, and PDFs\u003cbr\u003e- Explore LangChain Agents, OpenAgents, AutoGen frameworks\u003cbr\u003e- Monitor hallucinations, plan actions, and design recovery flows\u003cbr\u003e- Ensure safety, logging, and performance in agentic systems \u003cp\u003e\u003c\/p\u003e\u003cb\u003eProduction-Ready Deployment with Docker \u0026amp; Kubernetes\u003c\/b\u003e\u003cbr\u003e- Package LLMs and APIs into portable containers\u003cbr\u003e- Use docker-compose and Helm charts for orchestration\u003cbr\u003e- Deploy scalable clusters with GPU access and autoscaling\u003cbr\u003e- Implement health probes, registries, and versioned microservices \u003cp\u003e\u003c\/p\u003e\u003cb\u003eObservability, Evaluation \u0026amp; Continuous Delivery\u003c\/b\u003e\u003cbr\u003e- Monitor LLM drift, RAG relevance, and real-time model metrics\u003cbr\u003e- Run A\/B tests, feedback loops, and prompt re-ranking\u003cbr\u003e- Automate your ML pipelines using GitHub Actions + MLflow\u003cbr\u003e- Set up failover, alerts, and canary deployments \u003cp\u003e\u003c\/p\u003e\u003cb\u003eEthical and Global AI Deployment\u003c\/b\u003e\u003cbr\u003e- Handle bias, safety, privacy, and data sovereignty\u003cbr\u003e- Harden APIs against adversarial prompts and jailbreaking\u003cbr\u003e- Deploy inclusive systems across global and non-Western contexts\u003cbr\u003e\u003ci\u003eAmong others..\u003c\/i\u003e \u003cp\u003e\u003c\/p\u003e\u003cb\u003eBONUS\u003c\/b\u003e: Companion Project Repositories + Cheat Sheets\u003cbr\u003eReal projects: RAG chatbots, GraphRAG assistants, LLM agents\u003cbr\u003e\u003cb\u003eIf you're looking for a deeply practical, industry-relevant, and project-driven book to help you master modern AI engineering-this is it.\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e\u003cb\u003ePerfect for: \u003c\/b\u003e\u003cbr\u003e- AI\/ML engineers and full-stack developers\u003cbr\u003e- Backend engineers diving into LLMs and RAG\u003cbr\u003e- Technical founders building AI-powered products\u003cbr\u003e\u003cb\u003eJoin the future of AI development - become a practical AI Engineer.\u003c\/b\u003e","brand":"Atlantic Books","offers":[{"title":"Paperback","offer_id":46334302486679,"sku":"9798294142926","price":1825.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798294142926.webp?v=1768671853","url":"https:\/\/atlanticbooks.com\/products\/practical-ai-engineering-a-hands-on-guide-to-building-scalable-ai-with-python-llms-rag-tensorflow-pytorch-and-kubernetes-from-scratch-to-master-9798294142926","provider":"Atlantic Books","version":"1.0","type":"link"}