Books

AI Tools for Everyday Tasks: Beginner’s Guide shows how anyone can use today’s simple, affordable AI tools to reclaim 5–10 hours a week by working smarter, not harder. Written for busy professionals, students, and entrepreneurs with no technical background, the book offers clear, step-by-step guidance—no jargon or theory—on using AI to write emails and reports faster, create professional visuals without design skills, organize meetings automatically, learn new topics efficiently, and manage daily work with less stress, all supported by real-world examples, quick “try it now” exercises, and honest advice about what truly works.

Eric Zimmerman's Tools are free, open-source, and widely taught around the world. This is the official manual for all of his command line and GUI tools.

This book is about disrupting the status quo of all the governance crap you've seen, learnt and been told about before! I offer a refreshing, business focused view of what governance should really be about and how you can achieve governance to be proud of. You won't find platitudes or business-speak, just honest advice and guidance...

Which tech community title fits your expertise?Explore 33 recognition programs, learn how to qualify and apply, and turn meaningful contributions into professional visibility and new opportunities.

Turn your engineering team into a force multiplier, not a bottleneck. This book gives current and aspiring engineering managers practical frameworks, questions, and examples for everything from one on ones and feedback to scaling teams and navigating crises.

El libro abarca los conceptos de probabilidad, inferencia estadística, regresión lineal y machine learning. Les ayudará a desarrollar destrezas como programación en R, wrangling de datos, dplyr, visualización de datos, la creación de algoritmos, organización con UNIX, GitHub y la preparación de documentos con knitr y R markdown.

What if the real test of government isn't how much it spends, but what it leaves behind? The Sovereign Prosperity Framework challenges conventional political debate and explores how better decisions, stronger national capabilities and long-term stewardship can create lasting prosperity.

The Quantization Black Book The definitive engineering reference for 4-bit quantization of large language models — from 70B all the way to 400B parameters. Written for the people who actually have to fold these models onto real hardware and keep them fast, accurate, and deployable. This is not an overview. It is a deep technical field manual covering the full quantization stack: the math, the algorithms, the hardware setup, the calibration process, the runtime kernels, and the memory tricks that make the difference between a model that runs and a model that doesn't.

This book gives a brief, but rigorous, treatment of statistical inference intended for practicing Data Scientists.

Necati Ergin'in C++ ve İleri C++ kurslarındaki ders notlarından, kendisinin izniyle derlenmiş, iki ciltlik Türkçe başvuru kitabı. Cilt-I yeni mezun bireylere, Cilt-II ise daha kıdemli geliştiricilere hitap etmektedir. Kitap ücretsizdir ve ücretsiz kalacaktır.

Structure decays because it is expensive. This book shows how to make it cheap enough to keep: models as text, telemetry kept as a model, and no infrastructure beyond a JDK.

The AI revolution may not begin with a robot uprising. It may arrive quietly—when algorithms that influence our jobs, education, healthcare, and daily decisions become too essential to question.The Algorithmic Society explores who gets to set the rules of this new world—and whether we can still say no.

Micro platform architecture is a software architecture style that turns your software into a micro platform. Turning your software into a micro platform gives the users of your software greater flexibility in how they interact with your software. Your software could become simpler too – and the interaction with your software could become faster. There are other benefits to micro platform architecture too.

Understanding the most common mistakes in machine learning will allow you not only to avoid them, but to build better machine learning systems and less prone to errors. After reading this book, you will be ready to build more robust and trustworthy machine learning models.

GitOps has caused quite some fuss on Twitter and KubeCon, and still continues to do so. This book aggregates the essence of GitOps to help clear up the confusion. This book answers the following questions:What is GitOps?Why should I use GitOps?How does GitOps work?How to get started with GitOps on Kubernetes?What's the Future of GitOps?