Bøger udgivet af 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.

Learn the essential skills you need to pass the Cisco Certified Network Associate (CCNA) from the creator of one of the web's most popular CCNA video courses. Acing the CCNA Exam helps you prepare for and pass the CCNA exam by learning vital skills like: IPv4 and IPv6 addressing and subnetting Static and dynamic routing protocols (OSPF) Designing, configuring, and securing Ethernet LANs Designing, configuring, and securing Wireless LANs (Wi-Fi) Configuring essential network services like DHCP and DNS Fundamentals of network automation Acing the CCNA Exam is a comprehensive, detailed guide to passing the Cisco Certified Network Associate (CCNA) exam and kickstarting your career in IT, networking, and systems administration. It's written by Jeremy McDowell, a much-loved Cisco tutor who's amazing courses have helped hundreds of thousands of students pass their exams. Inside you'll find the secrets to nailing even the most perplexing exam topics. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology The CCNA is the gold standard entry-level certification for success in an IT career. Covering a range of networking technologies, the exam proves you know just what's needed to secure an entry-level job or advance your career. It certifies you as skilled in the fundamentals of networking--a vital skill across the tech industry--along with how to apply that knowledge on common Cisco hardware. It's the perfect stepping stone for a career in systems administration, server engineering, or cyber security. About the book Acing the CCNA Exam is full of must-know secrets that will help you ace one of the IT industry's most important exams the first time. This comprehensive study guide is geared towards the areas exam takers often find the most challenging. There's no assumption of knowledge and no high-level tech jargon. Handy network diagrams and illustrations fill every chapter to help learners easily understand the more complex topics. About the reader For absolute beginners. No networking skills required! About the author Jeremy McDowell is a senior network engineer, and an experienced teacher. Combining networking with his teaching skills, Jeremy has helped thousands of students study for and pass the CCNA exam through his YouTube channel Jeremy's IT Lab, which currently has over 220,000 subscribers.

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.

In a world of changing privacy regulations, identity theft, and online anonymity, identity is a precious and complex concept. Self-Sovereign Identity (SSI) is a set of technologies that move control of digital identity from third party identity providers directly to individuals, and it promises to be one of the most important trends for the coming decades. Now in Self-Sovereign Identity, privacy and personal data experts Drummond Reed and Alex Preukschat lay out a roadmap for a future of personal sovereignty powered by the Blockchain and cryptography. Cutting through the technical jargon with dozens of practical use cases from experts across all major industries, it presents a clear and compelling argument for why SSI is a paradigm shift, and shows how you can be ready to be prepared for it.

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

Quantum computing is on the horizon, ready to impact everything from scientific research to encryption and security. But you don't need a physics degree to get started in quantum computing. Quantum Computing for Developers shows you how to leverage your existing Java skills into writing your first quantum software so you're ready for the revolution. Rather than a hardware manual or academic theory guide, this book is focused on practical implementations of quantum computing algorithms. Using Strange, a Java-based quantum computer simulator, you'll go hands-on with quantum computing's core components including qubits and quantum gates as you write your very first quantum code. Key Features· An introduction to the core concepts of quantum computing· Qubits and quantum gates· Superposition, entanglement, and hybrid computing· Quantum algorithms including Shor's, Deutsch-jozsa, and Grover's search For Java developers at all levels who want an early start in quantum computing. No advanced math knowledge required. About the technology Whilst quantum hardware is still on the edge of development, the underlying principles for writing quantum software are well-established. Right now developers can utilize quantum simulators, like Java-based Strange, to try quantum experiments on any platform that runs the JVM. Johan Vosis a cofounder of Gluon, a Java technology company that aims to offer Java solutions for all platforms including desktop, embedded, and mobile apps, and connect them to the cloud. He is a Java Champion and holds an MSc in Mining Engineering and a PhD in Applied Physics.

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 how to handle errors, inefficiencies, and outdated paradigms by exploring the most common mistakes you’ll find in production C++ code.100 C++ Mistakes and How To Avoid Them reveals the problems you’ll inevitably encounter as you write new C++ code and diagnose legacy applications, along with practical techniques you need to resolve them. Inside 100 C++ Mistakes and How To Avoid Them you’ll learn how to: • Design solid classes • Minimize resource allocation/deallocation issues • Use new C++ features • Identify the differences between compile and runtime issues • Recognize C-style idioms that miss C++ functionality • Use exceptions well 100 C++ Mistakes and How To Avoid Them gives you practical insights and techniques to improve your C++ coding kung fu. Author Rich Yonts has been using C++ since its invention in the 1980s. This book distills that experience into practical, reusable advice on how C++ programmers at any skill level can improve their code. Unlike many C++ books that concentrate on language theory and toy exercises, this book is loaded with real examples from production codebases. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Over ten billion lines of C++ code are running in production applications, and 98-developers find and fix mistakes in them every day. Even mission-critical applications have bugs, performance inefficiencies, and readability problems. This book will help you identify them in the code you’re maintaining and avoid them in the code you’re writing. About the book 100 C++ Mistakes and How To Avoid Them presents practical techniques to improve C++ code, from legacy applications to modern codebases that use C++ 11 and beyond. Author Rich Yonts provides a concrete example to illustrate each issue, along with a step-by-step walkthrough for improving readability, effectiveness, and performance. Along the way, you’ll even learn how and where to replace outdated patterns and idioms with modern C++. What's inside • Design solid classes • Resource allocation/deallocation issues • Compile and runtime problems • Replace C-style idioms with proper C++ About the reader Covers C++ 98 through 23, with an emphasis on diagnosing and improving legacy code. About the author Rich Yonts is a Senior Software Engineer at Teradata and a long-time software engineer using C++, Java, and Python. He has held a number of technical and leadership roles during his many years at IBM and Sony. Table of Contents 1 C++: With great power comes great responsibility Part 1 2 Better modern C++: Classes and types 3 Better modern C++: General programming 4 Better modern C++: Additional topics Part 2 5 C idioms 6 Better premodern C++ Part 3 7 Establishing the class invariant 8 Maintaining the class invariant 9 Class operations 10 Exceptions and resources 11 Functions and coding 12 General coding

How do you know what might have happened, had you done things differently? Causal machine learning gives you the insight you need to make predictions and control outcomes based on causal relationships instead of pure correlation, so you can make precise and timely interventions.In Causal AI you will learn how to: Build causal reinforcement learning algorithms Implement causal inference with modern probabilistic machine tools such as PyTorch and Pyro Compare and contrast statistical and econometric methods for causal inference Set up algorithms for attribution, credit assignment, and explanation Convert domain expertise into explainable causal models Causal AI is a practical introduction to building AI models that can reason about causality. Author Robert Ness, a leading researcher in causal AI at Microsoft Research, brings his unique expertise to this cutting-edge guide. His clear, code-first approach explains essential details of causal machine learning that are hidden in academic papers. Everything you learn can be easily and effectively applied to industry challenges, from building explainable causal models to predicting counterfactual outcomes. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Causal machine learning is a major milestone in machine learning, allowing AI models to make accurate predictions based on causes rather than just correlations. Causal techniques help you make models that are more robust, explainable, and fair, and have a wide range of applications, from improving recommendation engines to perfecting self-driving cars. About the book Causal AI teaches you how to build machine learning and deep learning models that implement causal reasoning. Discover why leading AI engineers are so excited by causal reasoning, and develop a high-level understanding of this next major trend in AI. New techniques are demonstrated with example models for solving industry-relevant problems. You’ll learn about causality for recommendations; causal modeling of online conversions; and uplift, attribution, and churn modeling. Each technique is tested against a common set of problems, data, and Python libraries, so you can compare and contrast which will work best for you. About the reader For data scientists and machine learning engineers. A familiarity with probability and statistics will be helpful, but not essential, to begin this guide. Examples in Python. About the author Robert Ness is a leading researcher in causal AI at Microsoft Research. He is a contributor to open-source causal inference packages such as Python’s DoWhy and R’s bnlearn.

"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.

Get the big picture and the important details with this end-to-end guide for designing highly effective, reliable machine learning systems.From information gathering to release and maintenance, Machine Learning System Design guides you step-by-step through every stage of the machine learning process. Inside, you’ll find a reliable framework for building, maintaining, and improving machine learning systems at any scale or complexity. In Machine Learning System Design: With end-to-end examples you will learn: • The big picture of machine learning system design • Analyzing a problem space to identify the optimal ML solution • Ace ML system design interviews • Selecting appropriate metrics and evaluation criteria • Prioritizing tasks at different stages of ML system design • Solving dataset-related problems with data gathering, error analysis, and feature engineering • Recognizing common pitfalls in ML system development • Designing ML systems to be lean, maintainable, and extensible over time Authors Valeri Babushkin and Arseny Kravchenko have filled this unique handbook with campfire stories and personal tips from their own extensive careers. You’ll learn directly from their experience as you consider every facet of a machine learning system, from requirements gathering and data sourcing to deployment and management of the finished system. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Designing and delivering a machine learning system is an intricate multistep process that requires many skills and roles. Whether you’re an engineer adding machine learning to an existing application or designing a ML system from the ground up, you need to navigate massive datasets and streams, lock down testing and deployment requirements, and master the unique complexities of putting ML models into production. That’s where this book comes in. About the book Machine Learning System Design shows you how to design and deploy a machine learning project from start to finish. You’ll follow a step-by-step framework for designing, implementing, releasing, and maintaining ML systems. As you go, requirement checklists and real-world examples help you prepare to deliver and optimize your own ML systems. You’ll especially love the campfire stories and personal tips, and ML system design interview tips. What's inside • Metrics and evaluation criteria • Solve common dataset problems • Common pitfalls in ML system development • ML system design interview tips About the reader For readers who know the basics of software engineering and machine learning. Examples in Python. About the author Valerii Babushkin is an accomplished data science leader with extensive experience. He currently serves as a Senior Principal at BP. Arseny Kravchenko is a seasoned ML engineer currently working as a Senior Staff Machine Learning Engineer at Instrumental. Table of Contents Part 1 1 Essentials of machine learning system design 2 Is there a problem? 3 Preliminary research 4 Design document Part 2 5 Loss functions and metrics 6 Gathering datasets 7 Validation schemas 8 Baseline solution Part 3 9 Error analysis 10 Training pipelines 11 Features and feature engineering 12 Measuring and reporting results Part 4 13 Integration 14 Monitoring and reliability 15 Serving and inference optimization 16 Ownership and maintenance

Build resilient and scalable, cloud-native enterprise Java applications using the Quarkus framework.Quarkus lets you live-reload your Java code, deliver continuous background testing, and automatically provide database instances—plus tons more productivity-boosting features! Quarkus in Action quickly gets you up to speed with Quarkus by building a real-world business application. In Quarkus in Action, you will: • Use Quarkus Dev mode to speed up and enhance Java development • Understand how to use the Dev UI to observe and troubleshoot running applications • Automatic background testing using the Continuous Testing feature • New frameworks and libraries such as Quarkus Messaging, gRPC, and GraphQL • Simplify deployment of applications into Kubernetes and OpenShift • Automatic management of remote services such as databases and message brokers via Docker containers • Set up observability for applications by using metrics, health checks and distributed tracing Quarkus in Action is written by Martin Štefanko and Jan Martiška, Red Hat engineers who are both active contributors to the Quarkus project. In it, you’ll learn how Quarkus works and how you can integrate it into your stack for more productive Java development. Discover what makes Quarkus different from classic enterprise Java frameworks, how Quarkus streamlines creating cloud-native applications, and makes deployment easy. Foreword by Markus Eisele. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Choose a Java framework that’s as modern as your applications! Quarkus is a cloud-first framework designed for speed and cost optimization. It’s Kubernetes-aware by default and includes amazing productivity features like live reloading, continuous testing, and a developer-friendly UI that lets you code fluidly without tedious setup. About the book Quarkus in Action provides a carefully designed learning path through Quarkus’ key features and use cases. You’ll learn hands-on by implementing a working car rental application with a cloud-native microservices design that includes Kubernetes, SQL and NoSQL databases, messaging, and observability. Along the way, you’ll learn how Quarkus simplifies deployment on cloud platforms like OpenShift. What's inside • Speed up development with Quarkus Dev mode • Troubleshoot running apps with Dev UI • Continuous testing in the background • Automatic startup of development databases About the reader For intermediate Java developers who have experience deve- loping server-side Java applications. About the author Martin Štefanko and Jan Martiška are Red Hat engineers and active contributors to the Quarkus project. Table of Contents Part 1 1 What is Quarkus? 2 Your first Quarkus application 3 Enhancing developer productivity with Quarkus Part 2 4 Handling communications 5 Testing Quarkus applications 6 Exposing and securing web applications 7 Database access 8 Reactive programming 9 Quarkus messaging Part 3 10 Cloud-native application patterns 11 Quarkus applications in the cloud 12 Custom Quarkus extensions A Alternative languages and build tooling B Tools installations C Alternatives for developing frontend applications with Quarkus

Supercharge your applications with the ultimate guide to asynchronous and multithreaded programming in C#!C# Concurrency teaches you how to write effective multithreaded and asynchronous software in C#. Practical techniques, real-world examples, and useful code samples cut through the confusion around async/await and help you write rapid, reliable, and bug-free code. 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! In C# Concurrency Nir Dobovizki, a seasoned C# veteran with over 30 years of high-performance programming experience, shares his deep knowledge and expert techniques. 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! Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Asynchronous and multithreaded programs can perform multiple tasks simultaneously without losing speed or reliability. But getting concurrency right can challenge even experienced developers. This practical book teaches you to deliver concurrent C# apps that are lighting fast and free of the deadlocks and other synchronization issues that undermine performance and take forever to find. About the book C# Concurrency equips programmers with a comprehensive understanding of multithreading and asynchronous programming, focusing on the practical use of the C# async-await feature to simplify asynchronous tasks. It teaches how to avoid common pitfalls, addresses classic multithreading issues like deadlocks and race conditions, and advanced topics such as controlling thread of execution and using thread-safe collections. What's inside • .NET multithreading and asynchronous primitives • When to use concurrency techniques—and when not to! • Confidently use async/await About the reader For experienced C# programmers. No knowledge of asynchro- nous programming required. About the author Nir Dobovizki is a senior software architect and consultant who has worked on concurrent and asynchronous systems since the late 90s. Table of Contents 1 Asynchronous programming and multithreading 2 The compiler rewrites your code 3 The async and await keywords 4 Multithreading basics 5 async/await and multithreading 6 When to use async/await 7 Classic multithreading pitfalls and how to avoid them Part 2 8 Processing a sequence of items in the background 9 Canceling background tasks 10 Await your own events 11 Controlling on which thread your asynchronous code runs 12 Exceptions and async/await 13 Thread-safe collections 14 Generating collections asynchronously/await foreach and IAsyncEnumerable