A clear, illustrated guide to large language models, covering key concepts and practical applications. Ideal for projects, interviews, or personal learning.
Master language models through mathematics, illustrations, and code―and build your own from scratch!
You don’t need massive compute or big-tech resources to build real AI. This hands-on guide shows you how to build and fine-tune your own small language model—from scratch—using accessible tools like Google Colab. Learn transformers step-by-step, train and align models on your own data, and deploy practical AI systems that run on consumer GPUs. If you’ve ever wondered “Can I build my own model?”—this book proves the answer is yes.
Everything you really need to know in Machine Learning in a hundred pages.
A practical guide to product engineering in an AI native era, where building shifts from manual construction to steering tools, editors, and agents. Product Engineering with AI covers platforms, agentic workflows, prompting, code quality, UX, and responsible practices for getting from prototype to production.
Get started quickly, creating applications for the Model Context Protocol (MCP) using the official MCP SDKs for Python, Java 21, and Node.js. Quickly master, all of the concepts needed in order to build MCP servers, including transport protocols, tools, resources, prompts, roots, and sampling. Learn how to get familiar with popular MCP client applications such as, Claude Desktop, Postman, and the MCP Inspector.
AI engines are booming, and the more we work with agentic systems, the more we see that we need something to make them work at the enterprise level. We're quite active in exploring ideas around context graphs, decision traces, and supporting explainability—giving agents the ability to make more aware and company-aligned decisions.But this makes sense not only for enterprises, but for users and individuals building personal agents as well. Unfortunately, we have zero-to-none inclination on how to actually build a context graph.I'll try to explain how to build something like a context graph—but go beyond it. I deeply believe that to make this work, we need specific agentic memory and a set of cognitive processes that truly help agents use this memory and learn from experience and data.That's why this is the Book: Beyond Context Graphs—with a focus on real-life enterprise tasks and how to make agents make better decisions and, let's say, hallucinate less.
The book highlights the significance of software in systems engineering and uses AI as a subject matter expert. It presents a comprehensive example that covers SysML modeling, including requirements, use cases, logical/ physical architecture, and parametric simulation. It then continues into software, leveraging AI's code generation capabilities to produce software including microcontroller, UI, and DMBS code. It introduces a variety of personas and agents that can help engineers communicate with AI about systems and software engineering. The book also introduces SysML v2, focusing on the new language model and exploring AI's ability to generate models via code generation. Perhaps most importantly, it provides a straightforward roadmap for hardware/software co-design, accelerated at every step by AI. Whether you're a systems or software engineer, or just interested in how to use AI for engineering, AI Assisted MBSE with SysML will prove to be a valuable guide.
A strategic, executive-level guide to making the most of your company's AI efforts.
Revised for PyTorch 2.x! In 2019, I published a PyTorch tutorial on Towards Data Science and I was amazed by the reaction from the readers! Their feedback motivated me to write this book to help beginners start their journey into Deep Learning and PyTorch. I hope you enjoy reading this book as much as I enjoy writing it.
The essentials of making predictions using supervised regression and classification for tabular data. Tech stack: python, pandas, scikit-learn, CatBoost, LightGBM, XGBoost
Die meisten Unternehmen können schnell liefern, aber nur wenige können sich in großem Maßstab anpassen.The Cybernetic Enterprise stellt ein einheitliches Betriebsmodell vor, das KI, Rückkopplungsschleifen und Plattform-Denken in die DNA Ihrer Organisation einbettet. Erfahren Sie, wie Sie ein System aufbauen, das Veränderungen wahrnimmt, kontinuierlich lernt und Disruption in strategische Vorteile verwandelt.
Major capital projects keep missing the mark—over budget, behind schedule and under-delivering. Why? Because we’re still using delivery models designed for a different era. Rethinking Capital Project Delivery offers a bold, practical roadmap for fixing what’s broken. It introduces a new approach built on adaptive planning, intelligent systems and transparent governance. Instead of managing complexity with more layers, it shows how agentic AI and modular strategies can simplify, accelerate, and de-risk major works. This book is for executives, project leaders, and policymakers ready to move beyond outdated practices. If you know the system isn’t working—and you want to be part of the solution—this is your guide.
If you want to understand humanoid robotics at its core—this book is your roadmap.
Dette er en tempofyldt, praktisk og visuel guide til den mærkelige nye verden af Generativ AI. Den er som en udvidet version af Henriks virale video af samme navn. Trykt version: Paperback & hardback er tilgængelige på Amazon. Brug dit eget lands amazon-side (f.eks. Amazon.se for Sverige) for at minimere leveringstid og omkostninger.