manning publications jul 2025 (8 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware - Everything you need to know about AI to surviveand thriveas an engineer.If you're worried about your tech career going obsolete in a world of super-powered AI, never fear. The AI Pocket Book crams everything engineers need to know about AI into one short volume you can fit into your pocket. You'll build a better understanding of AI (and its limitations), learn how to use it more effectively, and future-proof your job against its advancement. In The AI Pocket Book you'll find no-nonsense advice on: Deciphering AI jargon (there's lots of it!) Where AI fits within your field of engineering Why AI hallucinatesand what to do about it What to do when AI comes for your job The dark side of AIcopyright, snake oil, and replacing humans Balancing skepticism with unrealistic expectations The AI Pocket Book gives you Emmanuel Maggiori's unvarnished and opinionated take on where AI can be useful, and where it still kind of sucks. Whatever your tech field, this short-and-sweet guide delivers the facts and techniques you'll need in the workplace of the present. About the technology You don't have to know everything about AI to get a big payoff! Whether you're looking to boost your coding speed, generate ideas for your next project, or just get a helping hand with your next Medium article, there's an AI-powered tool ready to assist. This fit-in-your pocket guide tells you everything you need to surf the AI wave instead of drowning in it. About the book The AI Pocket Book takes a peek inside the AI black box and gives you just enough on key topics like transformers, hallucinations, and the modern ecosystem of AI models and tools. You'll get handy techniques to select AI tools, learn when putting AI first is the smart move, and pick up some excellent tips for managing the inevitable, potentially expensive, screw ups. What's inside Deciphering AI jargon (there's lots of it!) Evaluating AI tools Why AI hallucinates and what to do about it How and when to use AI About the reader For engineers in all fields, from software to security. About the author Emmanuel Maggiori, PhD, is a software engineer and 10-year AI industry insider. He is also the author of Smart Until It's Dumb and Siliconned. Table of Contents 1 How AI works 2 Hallucinations 3 Selecting and evaluating AI tools 4 When to use (and not to use) AI 5 How AI will affect jobs and how to stay ahead 6 The fine print A Catalog of generative AI tools Get a free Elektronisches Buch (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.

Taschenbuch. Zustand: Neu. Neuware - Everything you need to know about Retrieval Augmented Generation in one human-friendly guide.Augmented Generationor RAGenhances an LLM's available data by adding context from an external knowledge base, so it can answer accurately about proprietary content, recent information, and even live conversations. RAG is powerful, and with A Simple Guide to Retrieval Augmented Generation, it's also easy to understand and implement! In A Simple Guide to Retrieval Augmented Generation you'll learn: The components of a RAG system How to create a RAG knowledge base The indexing and generation pipeline Evaluating a RAG system Advanced RAG strategies RAG tools, technologies, and frameworks A Simple Guide to Retrieval Augmented Generation gives an easy, yet comprehensive, introduction to RAG for AI beginners. You'll go from basic RAG that uses indexing and generation pipelines, to modular RAG and multimodal data from images, spreadsheets, and more. About the Technology If you want to use a large language model to answer questions about your specific business, you're out of luck. The LLM probably knows nothing about it and may even make up a response. Retrieval Augmented Generation is an approach that solves this class of problems. The model first retrieves the most relevant pieces of information from your knowledge stores (search index, vector database, or a set of documents) and then generates its answer using the user's prompt and the retrieved material as context. This avoids hallucination and lets you decide what it says. About the Book A Simple Guide to Retrieval Augmented Generation is a plain-English guide to RAG. The book is easy to follow and packed with realistic Python code examples. It takes you concept-by-concept from your first steps with RAG to advanced approaches, exploring how tools like LangChain and Python libraries make RAG easy. And to make sure you really understand how RAG works, you'll build a complete system yourselfeven if you're new to AI! What's Inside RAG components and applications Evaluating RAG systems Tools and frameworks for implementing RAG About the Readers For data scientists, engineers, and technology managersno prior LLM experience required. Examples use simple, well-annotated Python code. About the Author Abhinav Kimothi is a seasoned data and AI professional. He has spent over 15 years in consulting and leadership roles in data science, machine learning and AI, and currently works as a Director of Data Science at Sigmoid. Table of Contents Part 1 1 LLMs and the need for RAG 2 RAG systems and their design Part 2 3 Indexing pipeline: Creating a knowledge base for RAG 4 Generation pipeline: Generating contextual LLM responses 5 RAG evaluation: Accuracy, relevance, and faithfulness Part 3 6 Progression of RAG systems: Naïve, advanced, and modular RAG 7 Evolving RAGOps stack Part 4 8 Graph, multimodal, agentic, and other RAG variants 9 RAG development framework and further exploration Get a free Elektronisches Buch (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.

Taschenbuch. Zustand: Neu. Neuware - A hands-on guide for delivering value with AI-driven products! Learn how AI can improve content creation, accelerate data analysis, and upgrade process automation.The Art of AI Product Development offers a clear, practical approach to creating products that use AI. It provides real-world guidance on defining your AI strategy, developing useful AI features, and supporting user trust and adoption. Rather than chasing trends, the book focuses on core principles and long-term thinkingfoundations that remain relevant as the field evolves. Inside The Art of AI Product Development, you will learn vital skills for the effective use of AI, including: Identifying market and business opportunities for AI Gaining an in-depth understanding of modern AI approaches, incl. predictive AI, LLMs, Retrieval-Augmented Generation, and agent systems Assembling AI solutions that work, without the hype Efficiently communicating with data scientists and ML engineers Designing user-friendly AI interfaces that emphasize trust and transparency Implementing safe, ethical AI with proper governance processes The Art of AI Product Development is written for product managers, tech executives, UX designers, and anyone responsible for the success of an AI-driven product. It introduces a broad spectrum of AI opportunities and case studies from different domains such as marketing, supply chain, and logistics. You'll carefully progress from initial design conversations, through to efficient and secure development, and on to deployment and day-to-day management of AI-driven applications. About the technology Integrating AI into your software and processes can create real value for your business and its customersif you do it right. When you're on the hook for delivering AI-enabled products, you'll need to spot high-impact opportunities, work effectively with engineers, design user-centric features, avoid common project failures, and manage real-world launches. This book shows you how. About the book The Art of AI Product Development gives you a clear framework, practical tools, and real-world examples to build confidence and succeed with new AI projectseven if you're tackling AI for the first time. You'll love the practical use cases and end-to-end scenarios from domains such as marketing, supply chain management, and sustainability. What's inside Ideate, shape, and prioritize AI opportunities Develop AI systems with techniques such as prompt engineering, RAG, and predictive AI Communicate with different AI stakeholders and promote AI adoption About the reader Written for software product managers, business-oriented engineers, UX designers, startup founders, and anyone responsible for developing, designing, or marketing AI products. No experience with AI required. About the author Dr. Janna Lipenkova is the founder of an AI and analytics business where she has successfully managed AI projects for world-class companies like BMW, Lufthansa, and Volkswagen. Table of Contents Part 1 1 Creating value with AI-driven products 2 Discovering and prioritizing AI opportunities 3 Mapping the AI solution space Part 2 4 Predictive AI 5 Exploring and evaluating language models 6 Prompt engineering 7 Search and retrieval-augmented generation 8 Fine-tuning language models 9 Automating workflows with agentic AI Part 3 10 AI user experience: Designing for uncertainty 11 AI governance 12 Working with your stakeholders Appendix A AI development toolbox Get a free Elektronisches Buch (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.

Taschenbuch. Zustand: Neu. Neuware - Learn how to design web APIs that are a delight to use and maintain.Thousands of developers have followed renowned API expert Arnaud Lauret's guidance to create APIs that are flexible, secure, and easily integrated. This new edition of the bestselling The Design of Web APIs covers the latest updates to the OpenAPI standard, teaches you to streamline and standardize API design decisions with rationale and automation, and gives you insights you can apply to other API styles, such as gRPC. You'll quickly see how a well-designed and properly-documented API gives your users autonomyand saves you from constant explanations and hand-holding. This fully revised second edition of The Design of Web APIs teaches you the principles and techniques you need to design easy-to-consume public and private web APIs. In it, you'll learn how to: Analyze requirements to identify API capabilities for versatile, reusable designs Create HTTP-based REST APIs with CRUD, batch/bulk, or long operations Design interoperable, user-friendly APIs with seamless operations and data flow Ensure secure, efficient APIs while overcoming limitations and constraints Modify APIs without breaking compatibility, evaluating consequences carefully Future-proof your APIs and choose effective versioning strategies Document REST APIs using OpenAPI and JSON Schema for seamless implementation Streamline and standardize API design decisions with rationale and automation The Design of Web APIs, Second Edition teaches vital skills for gathering requirements, balancing business and technical goals and constraints, and adopting a consumer-first mindset. Each chapter is packed full of hands-on examples, including designing an Online Shopping API and user-friendly banking operations, and over seventy exercises to help your new skills stick. Plus, you'll explore paradigms applicable beyond REST APIs, and fully describe and document your APIs with OpenAPI and JSON Schema. Your web APIs will soon be easier to consume and your clientsinternal and externalwill be happier than ever! About the technology Web APIs open up your software to developers, exposing features, and capabilities to other programs. Well-designed web APIs are a joy. The bad ones are a nightmare, with endless impact on system performance, developer productivity, and end-user experience. This book shows you how to design APIs your fellow developers will love to use. About the book The Design of Web APIs, Second Edition teaches you to design efficient and adaptable REST APIs. This revised and rewritten second edition contains the latest updates to the OpenAPI standard, along with insights you can apply to other API styles such as GraphQL. Learn vital skills for gathering requirements, creating easy-to-consume public and private web APIs, and handling non-backward compatible modifications and versioning. What's inside Design reusable, user-friendly and interoperable APIs Document your APIs with OpenAPI and JSON Schema Create secure and efficient APIs by design Streamline and standardize API design decisions About the reader Written for developers with experience building and consuming APIs. About the author Arnaud Lauret runs the API Handyman blog and is a frequent speaker at API conferences. He currently works as an API Industry Researcher at Postman. Table of Contents 1 What is API design Part 1 2 Identifying API capabilities 3 Observing operations from the REST angle 4 Representing operations with HTTP 5 Modeling data 6 Describing HTTP operations with OpenAPI 7 Describing data with JSON Schema in OpenAPI Part 2 8 Designing user-friendly, interoperable data 9 Designing user-friendly, interoperable operations 10 Designing user-friendly, interoperable operation flows 11 Designing user-friendly, interoperable APIs Part 3 12 Designing a secure API 13 Designing an efficient API 14 Adapting the API design to the context 15 Modifying an API Part 4 16 Facilitating API design decision-making 17 Optimizing an OpenAPI document 18 Automating API design guidelines 19 Enriching API design artifacts A Solutions to the exercises Get a free Elektronisches Buch (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.

Taschenbuch. Zustand: Neu. Neuware.

Taschenbuch. Zustand: Neu. Neuware.

Taschenbuch. Zustand: Neu. Neuware - Go beyond the basics with this in-depth guide to quantum programming.Here's something you already know: quantum computing is a deep subject. Quantum Programming in Depth takes you beyond quantum basics and shows you how to take on practical quantum problem solving and programming using Q# and Qiskit. Author Mariia Mykhailova, a principal quantum applications software developer at PsiQuantum, guides you every step of the way. In Quantum Programming in Depth you'll explore: Algorithms to solve challenging quantum computing problems Writing quantum programs with Q# and Qiskit Testing quantum programs with simulators and specialized tools Evaluating performance of quantum programs on future fault-tolerant quantum computers Quantum Programming in Depth shows you how to do quantum computing outside the lab or classroom, presenting problems of quantum programming and demonstrating how they're solved. You'll learn to write quantum programs using Qiskit and Q#and even how to test your quantum code using common testing tools like pytest. You'll learn to prepare quantum states and implement operations, extract information from quantum states and operations, evaluate classical functions on a quantum computer, solve search problems, and more. About the Technology Going from the basic quantum concepts to developing software for quantum computers can be difficult! Algorithms that leverage quantum phenomena require new ways of thinking about computation and new approaches to writing code, testing it, and evaluating its performance. This book bridges the gap between QC theory and quantum programming in practice. About the Book Quantum Programming in Depth shows you how to solve quantum computing problems in a programmer-friendly way. The book's hands-on project-based approach will hone your quantum skills using realistic problems and progressively harder programming challenges. As you read, you'll design quantum algorithms and explore their performance on future fault-tolerant quantum computers. What's Inside Solve challenging quantum computing problems Write quantum programs with Q# and Qiskit Test quantum programs Evaluate performance of quantum programs About the Readers For students and software engineers who know Python and the basic concepts of quantum computing. About the Author Mariia Mykhailova is a principal quantum applications software developer at PsiQuantum. Table of Contents 1 Quantum computing: The hype and the promise Part 1 2 Preparing quantum states 3 Implementing quantum operations Part 2 4 Analyzing quantum states 5 Analyzing quantum operations Part 3 6 Evaluating classical functions on a quantum computer 7 Grover's search algorithm 8 Solving N queens puzzle using Grover's algorithm 9 Evaluating the performance of quantum algorithms A Setting up your environment Get a free Elektronisches Buch (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.

Taschenbuch. Zustand: Neu. Neuware - Discover all-practical implementations of the key algorithms and models for handling unlabeled data. Full of case studies demonstrating how to apply each technique to real-world problems. In Models and Algorithms for Unsupervised Learning you'll learn: