Manning Publications – serie

Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up! In  Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You'll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks. Build a Large Language Model (from Scratch) teaches you how to: Plan and code all the parts of an LLM Prepare a dataset suitable for LLM training Fine-tune LLMs for text classification and with your own data Use human feedback to ensure your LLM follows instructions Load pretrained weights into an LLM Build a Large Language Model (from Scratch) takes you inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you'll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant.   About the technology  Physicist Richard P. Feynman reportedly said, “I don't understand anything I can't build.” Based on this same powerful principle, bestselling author Sebastian Raschka guides you step by step as you build a GPT-style LLM that you can run on your laptop. This is an engaging book that covers each stage of the process, from planning and coding to training and fine-tuning.

A friendly, fully-illustrated introduction to the most important computer programming algorithms.

The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. This book will prepare you for those pesky algorithms questions in every programming job interview and help you apply them in your day-to-day work. And if you want to understand them without slogging through dense multipage proofs, this is the book for you.

In Grokking Algorithms, Second Edition you will discover:

Search, sort, and graph algorithms Data structures such as arrays, lists, hash tables, trees, and graphs NP complete and greedy algorithms Performance trade-offs between algorithms Exercises and code samples in every chapter Over 400 illustrations with detailed walkthroughs

The first edition of Grokking Algorithms proved to over 100,000 readers that learning algorithms doesn't have to be complicated or boring! This new edition now includes fresh coverage of trees, NP complete problems, and code updates to Python 3. With easy-to-read, friendly explanations, clever examples, and exercises to sharpen your skills as you learn, you’ll actually enjoy learning these important algorithms.

Build professional-grade full-stack web applications using C# and ASP.NET Core.

ASP.NET Core in Action, 3rd edition by Microsoft MVP Andrew Lock, is a fully updated edition, ideal for intermediate C# developers, and teaches you how to use your C# and .NET skills to build amazing cross-platform web applications. This revised bestseller reveals the latest .NET patterns, including minimal APIs and minimal hosting. Even if you have never worked with ASP.NET, you will soon start creating productive cross-platform web apps.

Features include:

Build minimal APIs for serving JSON to client-side applications Create dynamic, server-side rendered applications using Razor Pages User authentication and authorisation Store data using Entity Framework Core Unit and integration tests for ASP.NET Core applications Write custom middleware and components

About the technology

Developers love ASP.NET Core for its libraries and pre-built components that maximize productivity. This awesome web framework empowers you to build web applications using HTTP APIs, server-side rendered HTML, and long-running server processes - all by using the same familiar structure and components. Version 7.0 takes full advantage of new C# features, easy-to-build minimal APIs, and big performance upgrades.

Almost 50 years ago, the C language defined modern computer programming. This book shows you why C is still as powerful and popular as ever, with an inside look at the new C23 standard.For programs that need to be small, fast, and unfailingly reliable, C is still the gold standard. Whether you're writing embedded code, low-level system routines, or high-performance applications, C is up to the challenge. This unique book by Jens Gustedt, a member of the ISO C standards committee, gets you up to speed with C23.In Modern C, Third Edition you'll:

Learn C basics, core features, and advanced concepts Leverage major C23 improvements for security, reliability, and performance Write portable code that runs anywhere Build multi-threaded applications with atomics and synchronization Create robust and resilient software with error handling Use type-generic programming for reusable code

C powers more software than any other language—from embedded devices to distributed systems. In Modern C, Third Edition you'll learn to harness C's full potential using the latest tools and techniques. After a quick review of the fundamentals perfect for beginners or coders who haven't used C in a while, this book guides you to mastery of C23, the latest ISO standard.

Understanding Java from the JVM up gives you a solid foundation to grow your expertise and take on advanced techniques for performance, concurrency, containerization, and more. In  The Well-Grounded Java Developer, Second Edition you will learn: The new Java module system and why you should use it Bytecode for the JVM, including operations and classloading Performance tuning the JVM Working with Java's built-in concurrency and expanded options Programming in Kotlin and Clojure on the JVM Maximizing the benefits from your build/CI tooling with Maven and Gradle Running the JVM in containers Planning for future JVM releases The Well-Grounded Java Developer, Second Edition introduces both the modern innovations and timeless fundamentals you need to know to become a Java master. Authors Ben Evans, Martijn Verburg, and Jason Clark distil their decades of experience as Java Champions, veteran developers, and key contributors to the Java ecosystem into this clear and practical guide. about the technology

Java's history of innovation, its huge collection of libraries and frameworks, and the flexibility of the JVM have cemented its place as one of the world's most popular programming languages. Although it's easy to get started with Java, understanding how the language intersects with the JVM is the key to unlocking the power of this awesome language and its deep ecosystem of frameworks, tools, and alternative JVM-based languages. about the book

The Well-Grounded Java Developer, Second Edition is a complete revision of the classic original with the latest innovations of the Java platform. It upgrades your existing Java skills with both JVM fundamentals like bytecode, and powerful new features such as modules and concurrency models. You'll broaden your understanding of what's possible by exploring Kotlin and other JVM languages, and learn how functional programming can offer a powerful new perspective. Each concept is illustrated with hands-on examples, including a fully modularized application/library, build setups for Maven and Gradle, and creating your own multithreaded application.

Using large language models with your company’s internal data can be challenging. To create a trustworthy and stable solution, you need a system that is accurate, efficient, and secure. Building a prototype is one thing, but deploying a system that you can scale and maintain at an enterprise level requires a clear strategy. This book shows you how to build production-ready RAG systems that meet business demands. 

Build an enterprise-level RAG system that scales to meet demand.  Learn to use RAG with SQL databases and internal documentation.  Create fast and accurate searches for your applications.  Discover how to prevent AI hallucinations and inaccurate completions.  Monitor, scale, and maintain RAG systems in a cost-effective way. 

Enterprise RAG shows how to build reliable RAG systems for real use in organisations. The book draws on practical experience from real projects. It explains simple ways to improve search, refine questions, and get better results from your system. 

After reading this book, you will know how to sidestep common problems and handle challenges like choosing the right LLM. You will be able to build data workflows that maximise accuracy and address cost and performance issues. This book is for software developers who are proficient in Python and want to build reliable RAG solutions. 

Before you trust critical business systems to an AI model, you need to answer a few questions. Will it be fast enough? Will the system satisfy user expectations? Is it safe and can you trust the output? This book will help you answer these questions before you roll out an AI system, and make sure it runs smoothly after you deploy. 

Learn simple ways to test how your model behaves before it is used in real systems.  Try your model with real data to see how it performs in real situations.  Design A/B tests that validate model impact on key product metrics.  Spot nuanced failures with human-in-the-loop feedback and qualitative evaluations.  Use LLMs to help review and test models more quickly. 

AI Model Evaluation teaches you how to effectively evaluate and assess machine learning models for better scaling and integration. Each chapter looks at a different way to test a model, starting with offline evaluations and moving into live A/B tests, shadow traffic deployments and LLM-based feedback loops. The book uses a hands-on example grounded in a movie recommendation engine. 

After reading this book, you will be able to evaluate both model behaviour and engineering system performance. You will have the tools to ensure your AI systems are effective and reliable in production. This book is for practitioners with experience in machine learning, data science, or software engineering. 

Why wait to master deep learning when the tools are already within reach? As AI reshapes every industry, learning how to build models like GPT or generate stunning images is no longer a luxury—it is a necessity. Many developers struggle with fragmented tutorials or outdated libraries, leaving them unsure how to translate theory into practice. What if you could gain hands-on experience with the latest tools and techniques, backed by expert guidance, and build models that deliver real results from the start? 

First-principles walkthroughs: Understand every layer, activation, and optimizer, so troubleshooting feels natural.  Keras 3 showcase: Use the newest API features for faster, cleaner model pipelines.  Multiframework primer: Compare TensorFlow, PyTorch, and JAX to pick the right tool every time.  Generative AI chapters: Craft text with your own GPT-style model and create images using diffusion.  Production guidance: Learn scaling, tuning, and deployment tips that move notebooks into real apps. 

Deep Learning with Python, Third Edition, by François Chollet and Matthew Watson, delivers an authoritative, code-first roadmap from the minds behind Keras. 

Each chapter builds knowledge step by step, pairing intuitive explanations with color-coded listings you can run immediately. Expanded coverage tackles transformers, diffusion, and hardware-friendly workflows while retaining the approachable tone that made previous editions bestsellers. 

By the final page you will confidently architect, train, and fine-tune state-of-the-art models, ready to solve vision, language, and forecasting problems in your own projects. 

Ideal for developers with intermediate Python skills who crave practical, future-proof AI expertise.

Master the demand forecasting skills you need to decide what resources to acquire, products to produce, and where and how to distribute them.

For demand planners, S&OP managers, supply chain leaders, and data scientists. Demand Forecasting Best Practices is a unique step-by-step guide, demonstrating forecasting tools, metrics, and models alongside stakeholder management techniques that work in a live business environment.

You will learn how to:

Lead a demand planning team to improve forecasting quality while reducing workload Properly define the objectives, granularity, and horizon of your demand planning process Use smart, value-weighted KPIs to track accuracy and bias Spot areas of your process where there is room for improvement Help planners and stakeholders (sales, marketing, finances) add value to your process Identify what kind of data you should be collecting, and how Utilise different types of statistical and machine learning models

Follow author Nicolas Vandeput's original five-step framework for demand planning excellence and learn how to tailor it to your own company's needs. You will learn how to optimise demand planning for a more effective supply chain and will soon be delivering accurate predictions that drive major business value.

About the technology

Demand forecasting is vital for the success of any product supply chain. It allows companies to make better decisions about what resources to acquire, what products to produce, and where and how to distribute them. As an effective demand forecaster, you can help your organisation avoid overproduction, reduce waste, and optimise inventory levels for a real competitive advantage.

Use SQL to get the data you need in no time at all! Learn to read and write basic queries, troubleshoot common problems, and control your own business data in just 24 short lessons–no programming experience required! In  Learn SQL in a Month of Lunches you'll master useful SQL skills like: Write your own SQL queries See only the data you need in large datasets Easily filter, sort, and cluster data Master basic data manipulation techniques Safely create, update, and delete data Structured Query Language (SQL) is the standard way to get specific datasets out of large relational databases. If you use Excel, Tableau, or PowerBI to crunch business data, you've probably seen a lot of SQL already. And guess what? It's easy to master the most useful parts of SQL! In just a few quick lessons, you can learn to write your own queries, modify existing SQL statements, and add a new superpower to your bag of tricks. Learn SQL in a Month of Lunches introduces you to the most useful parts of SQL for business data analysis. This practical book gives you instantly-useful techniques starting from the first short chapter. 25-year SQL veteran Jeff Iannucci makes SQL a snap through hands-on lab exercises, relevant code examples, and easy-to-understand language.   About the technology   For decades, Structured Query Language has been the standard way to talk to relational databases. Unlike many programming languages, SQL is easy to read and understand once you get the hang of it. You don't need to be a data scientist—or even a tech professional—to master the most powerful features. For business data analysts, learning SQL empowers you to create better reports, uncover market insights, and freely explore large databases on your own.

Supercharge your applications with the ultimate guide to asynchronous and multithreaded programming in C#! In  C# Concurrency: Asynchronous and Multithreaded Programming you'll learn how to: Take full advantage of async/await Write bug-free multithreaded code every time Create multithreaded code that delivers real performance improvements Grok C# and .NET multithreading and asynchronous primitives Know when to use concurrency techniques—and when not to use them! C# Concurrency: Asynchronous and Multithreaded Programming teaches you to harness the power of multithreading and async/await to get maximum speed from your code. Nir Dobovizki, a seasoned C# veteran with over 30 years of high-performance programming experience, is here to share his deep knowledge and expert techniques with you. Say goodbye to frustrating pitfalls and impossible-to-find bugs that slow down your applications. Nir's careful approach will teach you how to navigate these challenges with ease, allowing you to achieve lightning-fast performance like never before!   About the technology:   Concurrency is a developers' secret weapon for maximizing an application's performance. Using asynchronous and multithreaded programming techniques, you can seamlessly execute multiple tasks simultaneously, without sacrificing speed or quality. However, concurrency is notoriously challenging to implement correctly due to the potential for race conditions, deadlocks, and other synchronization issues, and even an experienced developer can make mistakes that undermine their code's speed and introduce bugs that take forever to find.

Accelerate deep learning and other number-intensive tasks with JAX, Google’s awesome high-performance numerical computing library.In Deep Learning with JAX you will learn how to:

Use JAX for numerical calculations Build differentiable models with JAX primitives Run distributed and parallelized computations with JAX Use high-level neural network libraries such as Flax and Haiku Leverage libraries and modules from the JAX ecosystem

The JAX numerical computing library tackles the core performance challenges at the heart of deep learning and other scientific computing tasks. By combining Google’s Accelerated Linear Algebra platform (XLA) with a hyper-optimized version of NumPy and a variety of other high-performance features, JAX delivers a huge performance boost in low-level computations and transformations.Deep Learning with JAX is a hands-on guide to using JAX for deep learning and other mathematically-intensive applications. Google Developer Expert Grigory Sapunov steadily builds your understanding of JAX’s concepts. The engaging examples introduce the fundamental concepts on which JAX relies and then show you how to apply them to real-world tasks. You’ll learn how to use JAX’s ecosystem of high-level libraries and modules, and also how to combine TensorFlow and PyTorch with JAX for data loading and deployment.