Computer Programming/Artificial Intelligence/Python

A hands-on guide to downloading, running, serving, and maintaining open-weight LLMs on your own machine (492 manuscript pages).

AI engineering is becoming one of the most valuable and in-demand areas of software development, and Python, LangChain, and LangGraph are core skills for building the systems behind it. Learn how to turn basic Python knowledge into production-grade backend and agentic AI applications—and move toward an engineering niche centered on building and controlling AI rather than competing with it.

Learn to build production-ready LLM applications with DSPy through hands-on tutorials, complete runnable examples, and real-world projects. Master DSPy's core abstractions and create AI systems that improve with data instead of endless prompt tweaking.

A vendor-neutral, mechanism-level field guide to operating and extending agentic coding harnesses (542 manuscript pages).

Learn Claude Code by building real projects. This hands-on companion turns the Claude Code Masterclass workshop into a practical self-paced guide for planning, coding, testing, reviewing, refactoring, and shipping software with AI.

We'll stick to five libraries, not because more would be a problem, but because keeping it simple shows how well we can organise things. When you download MNIST with just the standard library, you finally see what a dataset loader was hiding. If you write attention as four lines of NumPy before you ever call a PyTorch module, it's no longer a magic process but just plain arithmetic.

The Python interview guide written from the interviewer's side of the table. 35 chapters. Every benchmark measured. Every line of code verified. What senior engineers actually get asked — and what separates the ones who get the offer.

You have built an AI agent that works beautifully in a demo, then falls apart the moment real users arrive: it invents answers, burns through tokens, and freezes on slow tools. The problem was never your prompt. This book shows you the real fix, layer by layer, and turns "I hope my agent works" into "I can prove it does."

A practical guide to operating a fleet of AI coding agents through routing, memory, skills, MCP, guardrails, and a persistent control plane (286 manuscript pages).

Go beyond calling transformer libraries and learn what actually happens under the hood. Starting from first principles, this book builds transformers from scratch with NumPy and PyTorch, then takes you through training, optimization and production inference. Along the way, you’ll work through the math, code and practical techniques behind modern transformer systems.

Designing AI is only half the journey. Learn how to deploy, secure, govern, monitor, and scale Enterprise AI systems for production with practical architectures and proven operational strategies.

PyTorch Deep Dive is a practical guide to mastering modern deep learning with PyTorch. From core concepts to advanced topics like transformers, diffusion models, and production deployment, it combines clear explanations, hands-on examples, and real-world best practices to help you build and scale AI applications with confidence.

MCP is the protocol powering the next generation of AI agents, and this is the only book that teaches you all of it. From Python fundamentals to low-level SSE transport, go from zero to production-ready MCP developer.

Teaser TextLearn AI by building real projects.Explore 10 practical beginner-level Artificial Intelligence projects and learn how to take an idea from problem definition to design, coding, testing, implementation, documentation, and future enhancement.From chatbots and face detection to resume screening, NLP, emotion detection, and intelligent recommendation systems, Vol-1 provides a structured introduction to practical AI development through the complete Software Development Life Cycle.Don’t just study AI. Build it.

Web Programming with Python and Flask: A Comprehensive Guide provides a structured and practical pathway into modern web development using one of Python’s most flexible and developer-friendly frameworks.Beginning with the fundamentals of web programming, the book guides readers through the complete Flask application-development journey—from installing Python and creating a development environment