Books

You want to analyse, understand and capture the subject matter of a domain, typically because you want to build a software system in that domain? You're looking for abstractions to describe and ultimately execute said subject matter? Then this book is for you: it's chock-full of experience and practices for tackling this challenge.

Do you need a high performance enterprise governance approach improving management, execution and delivery while dealing with multiple projects/products, events, stakeholders and teams? Giving you better bottom line results, faster time to market, less work, better predictability, happier employees, and delighted clients? Then learn about TameFlow!

Build a real, offline-first Android app in Elixir with Mob, from mix mob.new to an APK in your testers' hands, without leaving the BEAM.

A developer-friendly, practical and pragmatic guide to lightweight software architecture, technical leadership and the balance with agility.

The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. This book introduces concepts from probability, statistical inference, linear regression and machine learning and R programming skills. Throughout the book we demonstrate how these can help you tackle real-world data analysis challenges.

What if your software did not need the cloud to work? Local First Software Development shows you how to build fast, reliable apps that work offline and sync when needed. Learn practical patterns for data, security and synchronization while exploring how local-first systems can grow from simple personal tools into large collaborative applications.

Want to use NixOS "for real" at work? Interested in learning one of the hottest emerging DevOps technologies? Jumpstart your professional career by reading this book authored by a professional user of NixOS.

This thoroughly revised and expanded second edition demonstrates on over 800 pages how machine learning can add value to algorithmic trading in a practical yet comprehensive way. It has four parts that cover how to work with a diverse set of market, fundamental, and alternative data sources, design ML solutions for real-world trading challenges, and manage the strategy development process from idea to backtesting and evaluation.

From Mathematical Foundations to the Future of AIMost deep learning still lives in flat, Euclidean space. Real-world data does not.This 15-chapter university textbook takes you from the basics of topology and geometry to the frontier of Geometric Deep Learning, Topological Data Analysis, equivariant networks, and optimization on manifolds.Clear explanations. Worked examples. Research roadmaps.

MCP can transform the way you work with Claude Code. This practical guide takes you from the basics to production, showing you how to connect tools, build integrations, automate workflows and ship reliable, secure solutions you can use right away.

A practical, code-first guide to building production-ready AI agents and multi-agent systems in C# with Microsoft Agent Framework, Microsoft.Extensions.AI, tools, context, orchestration, observability, workflows, and enterprise-ready patterns.

Ready to build AI systems that work beyond the demo? This book takes you from the fundamentals to production-ready AI, covering everything from neural networks and LLMs to RAG, agents, optimization and deployment. Learn the theory, understand the code and gain the skills to build reliable AI systems from the ground up.

Language models guess. Knowledge graphs know. Rusty Graph shows you how to build a local AI agent whose memory is a real knowledge graph — typed, validated, reasoned over, and queryable with SPARQL — all inside a single static Rust binary. No JVM. No Docker sidecar. No Python runtime bolted to the side. You will build Ares a research-assistant agent that observes papers, forms beliefs, makes promises to other agents, and tracks the provenance of every fact it holds. Chapter by chapter, Ares grows from an empty Cargo workspace into a full pipeline: > load → reason → validate → query → answer All of it in under a thousand lines of idiomatic Rust, using three crates that actually work today: `oxigraph`, `reasonable`, and `rudof_lib`. `grapfeo` You will learn how to- Model a domain as RDF triples and load them into an embedded store. - Write RDFS and OWL 2 RL axioms that infer trust, identity, and inverse relationships — automatically. - Guard your graph with SHACL shapes that reject bad data at the boundary, not in production. - Query everything with SPARQL, from simple lookups to federated queries across named graphs. - Wire the graph into a hybrid RAG pipeline so your LLM answers are grounded in facts, not vibes. Who it is forRust developers building agents, assistants, or any system where the answer "the model said so" is not good enough. You should be comfortable with Cargo and traits. You do **not** need any prior semantic-web background — every concept is introduced through Ares before any formal definition appears. Why Rust, why nowLocal agents are the next deployment target: a user's laptop, a Raspberry Pi, a WASM sandbox. Python cannot go there comfortably. Rust can. This book is the missing manual for the Rust side of the semantic web — the one that tells you exactly which crates work, where the ecosystem is thin, and how to ship anyway. Stop hoping your model tells the truth. Give it a graph that does.

Mastering Advanced Time Series Forecasting in Python is the definitive sequel to the #1 forecasting bestseller. Designed for practitioners who want to go beyond ARIMA and basic ML, this book takes you deep into probabilistic forecasting, hierarchical coherence, and cutting-edge foundation models—backed by production-ready Python code. Learn how to assess forecastability, build scalable pipelines, quantify uncertainty, and deploy systems that deliver real business impact. Written by a globally recognized expert whose methods power multimillion-dollar decisions, this is the practical, honest, and advanced guide every data scientist, ML engineer, and quantitative professional needs to master modern forecasting.