Bøker utgitt av Manning Publications

Rust in Action introduces the Rust programming language by exploring numerous systems programming concepts and techniques. You'll be learning Rust by delving into how computers work under the hood. You'll find yourself playing with persistent storage, memory, networking and even tinkering with CPU instructions. The book takes you through using Rust to extend other applications and teaches you tricks to write blindingly fast code. You'll also discover parallel and concurrent programming.

KEY FEATURES* A great start with a great tutorial * Concise and easy-to-follow * Based on years of successful training techniques * Hands-on exercises and labs AUDIENCE Experience with Windows administration is helpful. No programming or scripting experience is assumed.

KEY SELLING POINTS Practical hands-on guide Quickly develop Spring applications Author insights based on years of Spring Development Covers newest features of Spring Boot AUDIENCE Written for readers familiar with the Spring Framework.

Take PowerShell beyond simple scripts and build time-saving automations for your team, your users, and the world.In Practical Automation with PowerShell you will learn how to:Build PowerShell functions to automate common and complex tasksCreate smart automations that are adaptable to new challengesStructure your code for sharing and reusabilityStore and secure your automationsExecute automations with Azure Automation, Azure Functions, and JenkinsShare your automations with your team and non-technical colleaguesStore and retrieve data, credentials, and variablesUse source control solutions to maintain and test code changesProvide front-end UI solutions for PowerShell automationsPractical Automation in PowerShell reveals how you can use PowerShell to build automation solutions for a huge number of common admin and DevOps tasks. It takes you beyond scripting basics and shows you how to handle the unforeseen complexities that can keep automations from becoming reusable and resilient. Youll discover tools and platforms that let you share your automations with your team and even roll them out to non-technical users through easy-to-understand Sharepoint frontends.

Unity inAction, Third Editionteaches you to writeand deploy games with Unity. Youll work through interesting and engagingexamples of 2D, 3D, and AR/VR games to get hands-on experience of Unitysintuitive workflow tools and state-of-the-art rendering engine. Joe Hockingsexpert instruction has given thousands of aspiring game developers a clearstarting point for their journey into Unity. Starting with the initialgroundwork of a new game development project, youll quickly progress tocreating scripts and building easy-to-read UIs. Now for the first time, thisfully updated third edition presents new coverage of Unitys XR toolkit andshows you how you can start building with virtual and augmented reality.

Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development.Summary Distributed across servers, difficult to test, and resistant to modification—modern software is complex. Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. It introduces a unique approach to functional programming that explains why certain features of software are prone to complexity, and teaches you the functional techniques you can use to simplify these systems so that they’re easier to test and debug. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Developers rightly fear the unintended complexity that infects most code. This book shows you how to write software that keeps complexity close to its inherent minimum. As you write software you should distinguish between code that alters your system’s state, and code that does not. Once you learn to make that distinction, you can refactor much of your state-altering “actions” into stateless “calculations.” Your software will be simpler. About the book The book also teaches you to solve the complex timing bugs that inevitably creep into asynchronous and multithreaded code. In ad­vanced sections of the book you learn how composable abstractions help avoid repeating code and open up new levels of expressivity. What's inside     Patterns for simpler code     Powerful time modeling approaches to simplify asynchronous code     How higher-order functions can make code reusable and composable About the reader For intermediate and advanced developers building complex software. Exercises, illustrations, self-assessments, and hands-on examples lock in each new idea. About the author Eric Normand is an expert software developer who has been an influential teacher of functional programming since 2007. Table of Contents 1 Welcome to Grokking Simplicity 2 Functional thinking in action PART 1 - ACTIONS, CALCULATIONS, AND DATA 3 Distinguishing actions, calculations, and data 4 Extracting calculations from actions 5 Improving the design of actions 6 Staying immutable in a mutable language 7 Staying immutable with untrusted code 8 Stratified design, part 1 9 Stratified design, part 2 PART 2 - FIRST-CLASS ABSTRACTIONS 10 First-class functions, part 1 11 First-class functions, part 2 12 Functional iteration 13 Chaining functional tools 14 Functional tools for nested data 15 Isolating timelines 16 Sharing resources between timelines 17 Coordinating timelines 18 Reactive and onion architectures 19 The functional journey ahead

Learn Kubernetes in a Month of Lunches is your guide to getting up and running with Kubernetes.Summary In Learn Kubernetes in a Month of Lunches you'll go from "what’s a Pod?" to automatically scaling clusters of containers and components in just 22 hands-on lessons, each short enough to fit into a lunch break. Every lesson is task-focused and covers an essential skill on the road to Kubernetes mastery. You'll learn how to smooth container management with Kubernetes, including securing your clusters, and upgrades and rollbacks with zero downtime. No development stack, platform, or background is assumed. Author Elton Stoneman describes all patterns generically, so you can easily apply them to your applications and port them to other projects! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Create apps that perform identically on your laptop, data center, and cloud! Kubernetes provides a consistent method for deploying applications on any platform, making it easy to grow. By efficiently orchestrating Docker containers, Kubernetes simplifies tasks like rolling upgrades, scaling, and self-healing. About the book Learn Kubernetes in a Month of Lunches is your guide to getting up and running with Kubernetes. You'll progress from Kubernetes basics to essential skills, learning to model, deploy, and manage applications in production. Exercises demonstrate how Kubernetes works with multiple languages and frameworks. You'll also practice with new apps, legacy code, and serverless functions. What's inside     Deploying applications on Kubernetes clusters     Understanding the Kubernetes app lifecycle, from packaging to rollbacks     Self-healing and scalable apps     Using Kubernetes as a platform for new technologies About the reader For readers familiar with Docker and containerization. About the author Elton Stoneman is a Docker Captain, a 11-time Microsoft MVP, and the author of Learn Docker in a Month of Lunches. Table of Contents PART 1 - FAST TRACK TO KUBERNETES 1 Before you begin 2 Running containers in Kubernetes with Pods and Deployments 3 Connecting Pods over the network with Services 4 Configuring applications with ConfigMaps and Secrets 5 Storing data with volumes, mounts, and claims 6 Scaling applications across multiple Pods with controllers PART 2 - KUBERNETES IN THE REAL WORLD 7 Extending applications with multicontainer Pods 8 Running data-heavy apps with StatefulSets and Jobs 9 Managing app releases with rollouts and rollbacks 10 Packaging and managing apps with Helm 11 App development—Developer workflows and CI/CD PART 3 - PREPARING FOR PRODUCTION 12 Empowering self-healing apps 13 Centralizing logs with Fluentd and Elasticsearch 14 Monitoring applications with Kubernetes with Prometheus 15 Managing incoming traffic with Ingress 16 Securing applications with policies, contexts, and admission control PART 4 - PURE AND APPLIED KUBERNETES 17 Securing resources with role-based access control 18 Deploying Kubernetes: Multinode and multiarchitecture clusters 19 Controlling workload placement and automatic scaling 20 Extending Kubernetes with custom resources and Operators 21 Running serverless functions in Kubernetes 22 Never the end

API Design Patterns lays out a set of design principles for building internal and public-facing APIs.Summary A collection of best practices and design standards for web and internal APIs. In API Design Patterns you will learn:     Guiding principles for API patterns     Fundamentals of resource layout and naming     Handling data types for any programming language     Standard methods that ensure predictability     Field masks for targeted partial updates     Authentication and validation methods for secure APIs     Collective operations for moving, managing, and deleting data     Advanced patterns for special interactions and data transformations API Design Patterns reveals best practices for building stable, user-friendly APIs. These design patterns can be applied to solve common API problems and flexibly altered to fit your specific needs. Hands-on examples and relevant use-cases illustrate patterns for API fundamentals, advanced functionalities, and even uncommon scenarios. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology APIs are contracts that define how applications, services, and components communicate. API design patterns provide a shared set of best practices, specifications and standards that ensure APIs are reliable and simple for other developers to use. This book collects and explains the most important patterns from both the API design community and the experts at Google. About the book API Design Patterns lays out a set of design principles for building internal and public-facing APIs. Google API expert JJ Geewax presents patterns that ensure your APIs are consistent, scalable, and flexible. You’ll improve the design of the most common APIs, plus discover techniques for tricky edge cases. Precise illustrations, relevant examples, and detailed scenarios make every pattern clear and easy to understand. What's inside     Guiding principles for API patterns     Fundamentals of resource layout and naming     Advanced patterns for special interactions and data transformations     A detailed case-study on building an API and adding features About the reader For developers building web and internal APIs in any language. About the author JJ Geewax is a software engineer at Google, focusing on Google Cloud Platform, API design, and real-time payment systems. He is also the author of Manning’s Google Cloud Platform in Action. Table of Contents PART 1 INTRODUCTION 1 Introduction to APIs 2 Introduction to API design patterns PART 2 DESIGN PRINCIPLES 3 Naming 4 Resource scope and hierarchy 5 Data types and defaults PART 3 FUNDAMENTALS 6 Resource identification 7 Standard methods 8 Partial updates and retrievals 9 Custom methods 10 Long-running operations 11 Rerunnable jobs PART 4 RESOURCE RELATIONSHIPS 12 Singleton sub-resources 13 Cross references 14 Association resources 15 Add and remove custom methods 16 Polymorphism PART 5 COLLECTIVE OPERATIONS 17 Copy and move 18 Batch operations 19 Criteria-based deletion 20 Anonymous writes 21 Pagination 22 Filtering 23 Importing and exporting PART 6 SAFETY AND SECURITY 24 Versioning and compatibility 25 Soft deletion 26 Request deduplication 27 Request validation 28 Resource revisions 29 Request retrial 30 Request authentication

Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated.Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you''ll discover just how effective and fun PyTorch can be. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Summary How can artificial intelligence transform your business? In Zero to AI, you'll explore a variety of practical AI applications you can use to improve customer experiences, optimize marketing, help you cut costs, and more. In this engaging guide written for business leaders and technology pros alike, authors and AI experts Nicolò Valigi and Gianluca Mauro use fascinating projects, hands-on activities, and real-world explanations to make it clear how your business can benefit from AI. About the technology There's no doubt that artificial intelligence has made some impressive headlines recently, from besting chess and Go grand masters to producing uncanny deep fakes that blur the lines of reality. But what can AI do for you? If you want to understand how AI will impact your business before you invest your time and money, this book is for you. About the book Zero to AI uses clear examples and jargon-free explanations to show the practical benefits of AI. Each chapter explores a real-world case study demonstrating how companies like Google and Netflix use AI to shape their industries. You begin at the beginning, with a primer on core AI concepts and realistic business outcomes. To help you prepare for the transition, the book breaks down a successful AI implementation, including advice on hiring the right team and making decisions about resources, risks, and costs. What's inside Identifying where AI can help your organization Designing an AI strategy Evaluating project scope and business impact Using AI to boost conversion rates, curate content, and analyze feedback Understanding how modern AI works and what it can/can't doAbout the reader For anyone who wants to gain an understanding of practical artificial intelligence and learn how to design and develop projects with high business impact. About the authors Gianluca Mauro and Nicolò Valigi are the cofounders of AI Academy, a company specializing in AI trainings and consulting. Table of Contents:1. An introduction to artificial intelligencePART 1 - UNDERSTANDING AI2. Artificial intelligence for core business data3. AI for sales and marketing4. AI for media5. AI for natural language6. AI for content curation and community buildingPART 2 - BUILDING AI7. Ready—finding AI opportunities8. Set—preparing data, technology, and people9. Go—AI implementation strategy10. What lies ahead

Key features * Jargon-free * Step-by-step guide * Real-world examples Audience This book provides a jargon-free introduction to Bitcoin for any technically interested reader. Some chapters address technical concepts that require basic knowledge of networking and programming.

Key features * Expert guidance * Hands-on examples * Step-by-step guide Audience If you're a C# developer who's comfortable working with the language and wants to really dig in deep, then this book is for you.

Speed up common data science tasks with AI assistants like ChatGPT and Large Language Models (LLMs) from Anthropic, Cohere, AI21, Hugging Face, and more!Using ChatGPT and other AI-powered tools, you can analyze almost any kind of data with just a few short lines of plain English. In LLMs in Action, you’ll learn important techniques for streamlining your data science practice, expanding your skillset and saving you hours—or even days—of time. Inside, you’ll learn how to use AI assistants to: • Analyze text, tables, images, and audio files • Extract information from multi-modal data lakes • Classify, cluster, transform, and query multimodal data • Build natural language query interfaces over structured data sources • Use LangChain to build complex data analysis pipelines • Prompt engineering and model configuration This practical book takes you from your first prompts through advanced techniques like building automated analysis pipelines and fine-tuning existing models. You’ll learn how to create meaningful reports, generate informative graphs, and much more. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the book LLMs in Action teaches you to use a new generation of AI assistants and Large Language Models (LLMs) to simplify and accelerate common data science tasks. Cornell professor and long-time LLM advocate Immanuel Trummer reveals techniques he’s pioneered for getting the most out of LLMs in data science, including model selection and specialization, techniques for tuning parameters, and reliable prompt templates. You’ll start with an in-depth exploration of how LLMs work. Then, you’ll dive into no-code data analysis with LLMs, creating custom operators with the OpenAI Python API, and building complex data analysis pipelines with the cutting edge LangChain framework. About the reader For data scientists, data analysts, and others who are interested in making their work easier through the use of artificial intelligence techniques. Readers should have a basic understanding of the Python programming language. About the author Immanuel Trummer is an assistant professor for computer science at Cornell University and leader of the Cornell Database Group. His papers have been selected for “Best of VLDB”, “Best of SIGMOD”, for the ACM SIGMOD Research Highlight Award, and for publication in CACM as CACM Research Highlight. Immanuel’s online course on data management has reached over a million views on YouTube. Over the past few years, his group has published extensively on projects that apply large language models in the context of data science.

A friendly illustrated guide to designing and implementing your first database.Data is the backbone of computer science, and databases are the main way that data is stored, exchanged, manipulated, and managed. Whether you’re a software developer, a data scientist, or an enthusiastic business user looking to up your data analysis skills, it pays to learn how to create and query relational databases like MySQL, SQL Server, PostgreSQL, and Oracle. Grokking Relational Database Design will get you started! In Grokking Relational Database Design, you’ll learn how to: • Query and create databases using Structured Query Language (SQL) • Design databases from scratch • Implement and optimize database designs • Take advantage of generative AI when designing databases A well-constructed database is easy to understand, query, manage, and scale when your app needs to grow. In Grokking Relational Database Design you’ll learn the basics of relational database design including how to name fields and tables, which data to store where, how to eliminate repetition, good practices for data collection and hygiene, and much more. You won’t need a computer science degree or in-depth knowledge of programming—the book’s practical examples and down-to-earth definitions are beginner-friendly. About the book Grokking Relational Database Design teaches the art of database design through real-world projects, insightful illustrations, and action-oriented learning. Unlike many beginning database books that focus on the technical details of SQL and formal database theory, this book teaches you how to think about relational database design from the ground up, so you’ll create databases that are a joy to use for a long time. Everything in this book is reinforced by hands-on exercises and examples. You’ll quickly design, implement, and optimize a database for an e-commerce application like the ones you use every day. You’ll also explore how generative AI tools such as ChatGPT radically simplify the mundane tasks of database design. About the reader Suitable for self-taught programmers, engineers, data scientists, and business data users. No previous experience with relational databases required. About the author Qiang Hao is an associate professor of Computer Science at Western Washington University. He is a recognized expert in computing education research and has extensive experience in teaching a variety of computer science courses, such as software engineering and database systems. Michail Tsikerdekis is an associate professor of Computer Science at Western Washington University. He holds a Ph.D. in Informatics from Masaryk University, Czechia. Additionally, he is recognized as an IEEE Senior Member, and his expertise covers over a decade of teaching experience in Computer Science and Cybersecurity.

"Learn to build standout line-of-business applications using Microsoft's .NET Framework, the premier platform for enterprise business development. Based on the bestselling .NET Core in Action, the new .NET in Action, Second Edition has been completely rewritten and updated by original author Dustin Metzgar--an industry veteran who helped develop both the original .NET Framework and .NET Core."-- Publisher provided description.

Tested and pragmatic methods for writing blogs, articles, and other technical pieces that stand out from the crowd!

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. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. 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. About the book Build a Large Language Model (From Scratch) is a practical and eminently-satisfying hands-on journey into the foundations of generative AI. Without relying on any existing LLM libraries, you’ll code a base model, evolve it into a text classifier, and ultimately create a chatbot that can follow your conversational instructions. And you’ll really understand it because you built it yourself! What's inside • Plan and code an LLM comparable to GPT-2 • Load pretrained weights • Construct a complete training pipeline • Fine-tune your LLM for text classification • Develop LLMs that follow human instructions About the reader Readers need intermediate Python skills and some knowledge of machine learning. The LLM you create will run on any modern laptop and can optionally utilize GPUs. About the author Sebastian Raschka is a Staff Research Engineer at Lightning AI, where he works on LLM research and develops open-source software. The technical editor on this book was David Caswell. Table of Contents 1 Understanding large language models 2 Working with text data 3 Coding attention mechanisms 4 Implementing a GPT model from scratch to generate text 5 Pretraining on unlabeled data 6 Fine-tuning for classification 7 Fine-tuning to follow instructions A Introduction to PyTorch B References and further reading C Exercise solutions D Adding bells and whistles to the training loop E Parameter-efficient fine-tuning with LoRA