Books

The code looks right. The agent sounds sure. Then it breaks. Learn the 50 most common ways AI-built apps fail, how to spot each one early, and how to fix it before your users find out.

A Comprehensive Engineering Guide to Low-Precision AI, Quantized Inference, GPU Kernels, and Production DeploymentQuantization is one of the key techniques for making large language models more efficient. By representing weights, activations, and other model data at reduced precision, engineers can lower memory requirements, improve hardware utilization, and potentially increase inference throughput. Achieving these benefits, however, requires careful trade-offs between numerical accuracy, computational cost, memory bandwidth, and hardware support. Mastering LLM Quantization: Architecture and Code is a 44-chapter engineering reference covering the mathematics, algorithms, implementation techniques, GPU kernels, evaluation methods, and deployment systems behind quantized language models. It connects theoretical foundations with practical approaches to building and optimizing low-precision inference pipelines.

This book will walk you through the best practices to use the indexes.

An in-depth, by examples ,look to the forgotten powerful tool .The jsonb type

If you are a database developer and you put performance as goal to achieve with your DB design...then using PL/PGSQL functions is your excellent tool.

Curious about agentic AI but not sure where to start? This beginner-friendly guide takes you from the basics to building your own AI agents, even if you have no coding experience. Learn how agents work, choose the right tools and turn your ideas into practical, reliable solutions for real-world problems.

Go from an empty window to a published open-source platformer. Python at Play teaches you to build, polish, test, and share real games with Python and pygame-ce, one runnable project at a time.

Learn Python the way it’s actually used at work. Start from zero, automate real office tasks, build APIs and data reports, and master the habits that turn a beginner into a hireable professional.

EmbeddingGemma 2 offers a hands-on look at Google's embedding model and how to put it to work. From semantic search and RAG to code retrieval and multimodal applications, this guide covers the architecture, trade-offs and practical implementation details you need to build reliable systems and make the right choices for your stack.

The battle-tested prompt framework and architectural system rules to turn any AI coding assistant into a principal full-stack engineer.

Building reliable distributed systems is harder than it looks. This book takes you from the fundamentals of message queues to the realities of distributed transactions, with working code, practical patterns and production lessons to guide you. Learn how to handle failures, maintain consistency and build systems that keep working when things go wrong.

Your AI application works on your machine. What happens when it reaches production? Learn to deploy, monitor, secure, and scale AI systems using Docker, CI/CD, Kubernetes, cloud infrastructure, and practical production engineering. Move beyond prototypes and build AI applications you can operate with confidence.

Build AI inference systems that run fast, use less memory and keep your data where it belongs. This hands-on guide walks you through model deployment, performance tuning, security and production engineering with practical code and real benchmarks. No cloud dependency, no surprise bills, just efficient AI systems you control.

You can generate code faster than you can review it. That asymmetry is the real challenge of AI-assisted development — and almost nobody talks about it. Vibe Coding with OpenCode teaches the other half of the skill: not how to make AI write code, but how to make AI write code you can actually trust.

Go from your first MATLAB script to professional engineering projects. Master programming, data analysis, visualization, numerical computing, and AI-assisted workflows through practical, project-based learning.