Books

اكتشف كيف يمكن للذكاء الاصطناعي التوليدي أن يصبح شريكك في التعليم، مع قوالب جاهزة وأمثلة عملية تساعدك على الابتكار داخل الصف الدراسي.

Kotlin Recipes for Android Developers delivers practical solutions to real-world coding challenges in Android. Covering null-safety, coroutines, Flow, Jetpack libraries, and Compose, this book shows you how to apply idiomatic Kotlin techniques to write clean, efficient, and maintainable apps. Designed for developers who want actionable answers, it’s a hands-on guide to building robust Android software with modern Kotlin practices.

So how do you make an AI agent and conversational agent understand time? How does time shape attention? How is time important for the context engine? You will learn how to add time to knowledge graphs, how time and causality drive context, and how to make the knowledge graphs that are used for AI memory time-aware.

Whether you're healing from heartbreak, celebrating love, or simply searching for meaning, Love Unfolded will touch your soul and remind you that love, in all its forms, is worth unfolding.

Unlock the full potential of modern Angular with Signals ... now stable in Angular v22. Angular's reactivity model is going through its biggest shift yet, and Signals are at the heart of it: simpler, faster, more predictable apps. This fully updated guide takes you from the fundamentals to advanced mastery ... the core signal, computed, and effect, the new linkedSignal, resource/httpResource, and Signal Forms ... plus a practical path for migrating off Zone.js and RxJS.

Not Artificial, Not Intelligent cuts through the hype and doom to show what AI really is: powerful pattern-matching infrastructure, not thinking machines. Forget sci-fi fantasies - this is AI realism, explaining how machine learning is already reshaping business and culture.

Sharpen your knowledge for the CIPP/E exam with 90 practice questions and detailed explanations. Updated September 2025, this guide covers all exam domains and helps you succeed with confidence.

This handbook is a practical, hands-on guide for Master’s students in Business and Marketing. It provides step-by-step support for every stage of the research journey: from choosing a topic and reviewing the literature to designing frameworks, selecting methods, analyzing data, and writing up results. Unlike generic textbooks, this guide focuses on practical tools, examples, and checklists that students can apply immediately. With integrated resources on SPSS, NVivo, MAXQDA, SmartPLS, Jamovi, R, and AI research tools (Consensus, Elicit, ResearchRabbit), it bridges theory and practice, helping students move from confusion to clarity. A must-have companion for anyone who wants to successfully complete a thesis in business and marketing.

AI is changing not only what architects build, but what it means to be an architect.Dear Software and AI Architect is a practical guide for software architects and emerging AI architects who want to navigate ambiguity, make better trade offs, design intelligent systems people can trust, and connect architecture decisions to real business impact.Inside, you’ll find 50+ practical caselets, expert perspectives, field tested lessons, and the Architect’s V Impact Canvas to help you build with context and lead with clarity as software and AI engineering converge.The book draws on my more than two decades of experience working with complex software, cloud, platform, and AI systems, translating lessons from the field into ideas you can apply in your own architecture journey.And decorating this journey is a foreword by my mentor, Grady Booch, UML co creator and one of the most influential voices in software architecture.This is not a book about chasing AI hype. It is about becoming the architect this new era demands.

How to represent knowledge for LLMs and build memory for agents, I discovered Mark's work on semantic spacetimes. It's more of a theoretical framework from someone who came from physics. But actually, jumping to knowledge representation and reasoning, and trying to answer the question of how to build dynamic and complex systems—semantic spacetimes and promise theories are crucial for the future of agentic systems, in my belief.The semantic spacetime approach gives us answers on how to organize better memory and how to have better knowledge representation that could be understood quite well by LLMs. Vector embeddings actually create a lot of challenges—some spaces and some relations in vector embeddings simply don't exist. We all have this problem where "love my wife " and "hate my wife" while actually quite distant in practice, and also time and dynamics matter