Books

Teaser TextEnter the world of advanced AI engineering.Volume 4 presents 10 advanced Artificial Intelligence projects covering medical diagnosis, crime prediction, autonomous drones, predictive maintenance, disaster management, conversational AI, financial fraud detection, legal document analysis, smart shopping, and autonomous vehicle vision.Go beyond basic models and explore how complex AI systems can be planned, designed, developed, tested, deployed, and enhanced using a complete Software Development Life Cycle.From intelligent models to intelligent systems.

Teaser TextBuild smarter AI solutions for real-world problems.Volume 3 presents 10 intermediate-level AI projects covering intelligent tutoring, wildlife detection, healthcare scheduling, air-quality prediction, career recommendations, fire detection, adaptive e-learning, conversational AI, movie recommendations, and resume skill extraction.Each project follows the complete Software Development Life Cycle, helping readers move from problem identification and system design to AI development, testing, implementation, and future enhancement.Turn AI concepts into intelligent applications.

Teaser TextTake your AI projects to the next level.Explore 10 intermediate-level Artificial Intelligence projects covering NLP, Machine Learning, Computer Vision, prediction, classification, sentiment analysis, image recognition, and voice-based applications.From fake news detection and student performance prediction to resume ranking, plant disease identification, sign language recognition, and language translation, Vol-2 takes you deeper into practical AI development through a complete Software Development Life Cycle.Learn the concepts. Build the systems. Think like an AI 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.

Running LLMs locally is easy. Running them well is an engineering problem. Practical LLM Inference gets into the details that matter, from quantization and GGUF internals to GPU offloading, benchmarking and production deployment. Learn how to size hardware, find bottlenecks and build fast, reliable inference systems without the AI hand-waving.

Most vector search books start with the database. This one starts with the machine. Build a search engine from scratch, then push it from brute force to billion-scale retrieval with SIMD, HNSW, quantization and distributed systems. By the end, vector search won't be a black box. It'll be something you know how to build, tune and scale.

AI can write code in seconds, but can you trust what it creates? Securing AI-Generated Code shows you how to uncover hidden vulnerabilities, stop risky dependencies, secure AI coding agents and build safer development pipelines. A practical guide for teams that want the speed of AI without putting security on the line.

Stop building brittle LLM wrappers and start engineering production-grade autonomous agent networks.This hands-on guide takes you from fundamental Transformer mechanics to orchestrating multi-agent architectures under Kubernetes with Python. Step beyond basic prototypes to master graph-based orchestration, grammar-constrained outputs, LoRA fine-tuning, RAG, and MCP. Learn to navigate critical production trade-offs—model routing, quantization, cost control, prompt injection security, and human-in-the-loop monitoring—to deploy resilient, enterprise-ready AI systems.

Building fast LLM systems takes more than a powerful GPU. This book shows you what actually happens between prompt and response, where latency hides and how to fix it. Work from kernels and inference engines to distributed clusters, benchmarking and production reliability, with practical guidance for building systems that stay fast under real-world load.

Legacy modernization is an evidence problem before it is a code-generation problem. Use Claude Code to recover hidden behavior, build a verification harness, and move critical systems in controlled, reversible slices without handing production decisions to AI. Includes 26 practical chapters, 86 diagrams, and a runnable companion lab.

The definitive production architecture transmission from Seeker James. The semantic frequencies are locked, the structural codes are captured, and the technical metadata is anchored under ABN 52 464 760 231. This official codex spans 77 pages, stripping away mainstream corporate industry polish to reveal a tight, high-impact collection of raw technical truth.

They say AI is coming for junior developers first. This is a junior's honest case for the opposite: how driving agents well, on real legacy code, makes you level up faster instead of getting left behind. The failures are left in.

ChatGPT can save you time, sharpen your ideas and change the way you work, but only if you know how to use it well. This practical guide takes you from your first prompt to advanced techniques, with real-world examples for writing, research, coding, business and creativity. Learn what works, what doesn’t and how to get better results every day.

Unlock the full potential of Qwen 3.8 with a practical guide built for real results. Learn the techniques behind stronger prompts, avoid common mistakes, and create reliable outputs for coding, research, business, creative projects and AI agents with clear examples you can use right away.

Build MCP servers that are ready for real production. This hands on guide shows you how to design, secure, deploy and operate stateless Model Context Protocol servers that scale with confidence. Packed with practical examples and proven patterns, it gives you the skills to build reliable AI infrastructure from the ground up.