Books

هذا الكتاب هو دليل مختصر وموضّح بالرسوم لأي شخص يرغب في فهم الآلية الداخلية للنماذج اللغوية الضخمة، سواء في سياق المقابلات أو المشاريع أو بدافع الفضول الشخصي.

The practitioner's guide to policy-space response oracles: one 84-line loop, one readable repository, and every claim backed by a committed experiment — including the ones that came out wrong.

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.

Explore the foundations and future of modern computing—from artificial intelligence and distributed systems to cybersecurity, quantum technologies, and responsible computing. Modern Computer Science connects essential concepts with emerging technologies, real-world applications, and the challenges shaping the future of the discipline.

Master LTX 2.5 from the first prompt to the final shot. Learn to create cinematic video with synchronized audio, precise camera movement and consistent characters while avoiding the mistakes that waste time and generations. Built on official documentation and verified behavior, this is a practical guide to getting production-ready results from LTX 2.5.

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.

Use LoRA because it forgets less. Keep the learning rate low. Mix in some general data. Stopearly. Four pieces of advice everyone repeats and almost nobody quantifies. This book measures each one — and two turn out to be doing something other than what they arecredited with. LoRA's retention is governed by a scaling constant, not by its parameterefficiency. Early stopping bounds the damage without separating it from the gain. Everyexperiment reports two numbers: the new task, and the capability you were not trying tochange.

The model is only half the system. Learn to design the scaffolding, tools, sandboxes, verification loops, and memory that turn raw LLMs into reliable, production-grade AI agents that actually finish the job.

A hands-on guide to Anthropic's command-line AI coding assistant. Learn to install, converse with, and steer Claude Code through file edits, testing, debugging, refactors, and Git workflows, then build a real project from scratch and connect it to external tools with MCP.

The AI Advantage shows you how to use artificial intelligence to work smarter, create more, save time, boost productivity, and discover new opportunities—even if you’re completely new to AI. With practical tools, strategies, examples, and prompts, you’ll learn how to turn AI into a powerful advantage for your personal and professional growth.

AI has entered the programming picture, let's learn how to be humans working with AI to build better software, together.