Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory. Engineers, data scientists, and students alike will examine mathematical topics critical for AI--including regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more--through popular applications such as computer vision, natural language processing, and automated systems. And supplementary Jupyter notebooks shed light on examples with Python code and visualizations. Whether you're just beginning your career or have years of experience, this book gives you the foundation necessary to dive deeper in the field. Understand the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and more Learn how to adapt mathematical methods to different applications from completely different fields Gain the mathematical fluency to interpret and explain how AI systems arrive at their decisions.
With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and more explainable. Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the academic literature for curating datasets and building models into a blueprint for building industry-grade trusted ML systems. With this book, engineers and data scientists will gain a much-needed foundation for releasing trustworthy ML applications into a noisy, messy, and often hostile world. You'll learn: Methods to explain ML models and their outputs to stakeholders How to recognize and fix fairness concerns and privacy leaks in an ML pipeline How to develop ML systems that are robust and secure against malicious attacks Important systemic considerations, like how to manage trust debt and which ML obstacles require human intervention
Good software design is essential for the success of your project, but designing software is hard to do. You need to have a deep understanding of the consequences of design decisions and a good overview of available design alternatives. With this book, experienced C++ developers will get a thorough, practical, and unparalleled overview of software design with this modern language.C++ trainer and consultant Klaus Iglberger explains how you can manage dependencies and abstractions, improve changeability and extensibility of software entities, and apply and implement modern design patterns to help you take advantage of today's possibilities. Software design is the most essential aspect of a software project because it impacts the software's most important properties: maintainability, changeability, and extensibility.Learn how to evaluate your code with respect to software designUnderstand what software design is, including design goals such as changeability and extensibilityExplore the advantages and disadvantages of each design approachLearn how design patterns help solve problems and express intentChoose the right form of a design pattern to get the most out of its advantages
This book, designed for anyone interested in building knowledge graphs, equips you with everything you need to start building your own knowledge graphs. You'll learn about common patterns for knowledge graphs, with hands-on examples to work through.
In this insightful and entertaining book, Michael Lopp recalls his own make-or-break moments with Silicon Valley giants such as Apple, Slack, Pinterest, Palantir, Netscape, and Symantec to help you make better, more mindful career decisions.
With this updated third edition, you'll quickly learn how to be productive with Ansible whether you're a developer deploying code or a system administrator looking for a better automation solution.
Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This revised third edition--updated for Cassandra 4.0 and new developments in the Cassandra ecosystem, including deployments in Kubernetes with K8ssandra--provides technical details and practical examples to help you put this database to work in a production environment.Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. Developers, DBAs, and application architects looking to solve a database scaling issue or future-proof an application will learn how to harness Cassandra's speed and flexibility.Understand Cassandra's distributed and decentralized structureUse the Cassandra Query Language (CQL) and cqlsh (the CQL shell)Create a working data model and compare it with an equivalent relational modelDesign and develop applications using client driversExplore cluster topology and learn how nodes exchange dataMaintain a high level of performance in your clusterDeploy Cassandra onsite, in the cloud, or with Docker and KubernetesIntegrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene
Take your Linux skills to the next level! Whether you're a system administrator, software developer, site reliability engineer, or enthusiastic hobbyist, this practical, hands-on book will help you work faster, smarter, and more efficiently. You'll learn how to create and run complex commands that solve real business problems, process and retrieve information, and automate manual tasks. You'll also truly understand what happens behind the shell prompt, so no matter which commands you run, you can be more successful in everyday Linux use and more competitive on the job market. As you build intermediate to advanced command-line skills, you'll learn how to: Choose or construct commands that get your work done quickly Run commands efficiently and navigate the Linux filesystem with ease Build powerful, complex commands out of simpler ones Transform text files and query them like databases to achieve business goals Control Linux point-and-click features from the command line
Testing is a critical discipline for any organization looking to deliver high-quality software. This practical book provides software developers and QA engineers with a comprehensive one-stop guide to testing skills in 10 different categories. You'll learn appropriate strategies, concepts, and practical implementation knowledge you can apply from both a development and testing perspective for web and mobile applications.Author Gayathri Mohan offers examples of more than 40 tools you can use immediately. You'll acquire the skills to conduct exploratory testing, test automation, cross-functional testing, data testing, mobile testing, and visual testing, as well as tests for performance, security, and accessibility. You'll learn to integrate them in continuous integration pipelines to gain faster feedback. Once you dive into this guide, you'll be able to tackle challenging development workflows with a focus on quality.With this book, you will:Learn how to employ various testing types to yield maximum quality in your projectsExplore new testing methods by following the book's strategies and conceptsLearn how to apply these tools at work by following detailed examplesImprove your skills and job prospects by gaining a broad exposure to testing best practices
Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world.Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI.This book examines:Differences between and limitations of automated, autonomous, and human decision-makingUnique advantages of autonomous AI for real-time decision-making, with use casesHow to design an autonomous AI from modular components and document your designs
Kubernetes is the operating system of the cloud-native world, providing a reliable and scalable platform for running containerized workloads. This book shows developers and operations staff how to apply industry-standard DevOps practices to Kubernetes in a cloud-native context.
Shell scripts are everywhere, especially those written in bash-compatible syntax. But these scripts can be complex and obscure. Complexity is the enemy of security, but it's also the enemy of readability and understanding. With this practical book, you'll learn how to decipher old bash code and write new code that's as clear and readable as possible.Authors Carl Albing and JP Vossen show you how to use the power and flexibility of the shell to your advantage. You may know enough bash to get by, but this book will take your skills from manageable to magnificent. Whether you use Linux, Unix, Windows, or a Mac, you'll learn how to read and write scripts like an expert. Your future you will thank you.You'll explore the clear idioms to use and obscure ones to avoid, so that you can:Write useful, flexible, and readable bash code with styleDecode bash code such as ${MAKEMELC,,} and ${PATHNAME##*/}Save time and ensure consistency when automating tasksDiscover how bash idioms can make your code clean and concise
You'll find several books on basic or advanced MySQL performance, but nothing in between. That's because explaining MySQL performance without addressing its complexity is difficult. This practical book bridges the gap by teaching software engineers mid-level MySQL knowledge beyond the fundamentals, but well shy of deep-level internals required by database administrators (DBAs).Daniel Nichter shows you how to apply the best practices and techniques that directly affect MySQL performance. You'll learn how to improve performance by analyzing query execution, indexing for common SQL clauses and table joins, optimizing data access, and understanding the most important MySQL metrics. You'll also discover how replication, transactions, row locking, and the cloud influenceMySQL performance.Understand why query response time is the North Star of MySQL performanceLearn query metrics in detail, including aggregation, reporting, and analysisSee how to index effectively for common SQL clauses and table joinsExplore the most important server metrics and what they reveal about performanceDive into transactions and row locking to gain deep, actionable insightAchieve remarkable MySQL performance at any scale
The cloud is becoming the de facto home for companies ranging from enterprises to startups. Moving to the cloud means moving your applications from monolith to microservices. But once you do, running and maintaining these services brings its own level of complexity. The answer? Modularity, deployability, observability, and self-healing capacity through cloud native development.With this practical book, Nishant Singh and Michael Kehoe show you how to build a true cloud native infrastructure using Microsoft Azure or another cloud computing solution by following guidelines from the Cloud Native Computing Foundation (CNCF). DevOps and site reliability engineers will learn how adapting applications to cloud native early in the design phase helps you fully utilize the elasticity and distributed nature of the cloud.This book helps you explore:Why go cloud native?How to use infrastructure as codeWhat it takes to containerize an applicationWhy and how Kubernetes is the "e;grand orchestrator"e;How to create a Kubernetes cluster on AzureHow observability complements monitoringHow to use service discovery and a service mesh to find new territoriesHow networking and policy management serve as gatekeepersHow distributed databases and storage work
The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations.Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data.Use Python 3.8+ to read, write, and transform data from a variety of sourcesUnderstand and use programming basics in Python to wrangle data at scaleOrganize, document, and structure your code using best practicesCollect data from structured data files, web pages, and APIsPerform basic statistical analyses to make meaning from datasetsVisualize and present data in clear and compelling ways
Observability is critical for building, changing, and understanding the software that powers complex modern systems. Teams that adopt observability are much better equipped to ship code swiftly and confidently, identify outliers and aberrant behaviors, and understand the experience of each and every user. This practical book explains the value of observable systems and shows you how to practice observability-driven development.Authors Charity Majors, Liz Fong-Jones, and George Miranda from Honeycomb explain what constitutes good observability, show you how to improve upon what you??re doing today, and provide practical dos and don'ts for migrating from legacy tooling, such as metrics monitoring and log management. You??ll also learn the impact observability has on organizational culture (and vice versa).You'll explore:How the concept of observability applies to managing software systemsThe value of practicing observability when delivering and managing complex cloud native applications and systemsThe impact observability has across the entire software development lifecycleHow and why different functional teams use observability with service-level objectives (SLOs)How to instrument your code to help future engineers understand the code you wrote todayHow to produce quality code for context-aware system debugging and maintenanceHow data-rich analytics can help you debug elusive issues quickly
How can you realize MySQL's full power? With High Performance MySQL, you'll learn advanced techniques for everything from setting service-level objectives to designing schemas, indexes, and queries to tuning your server, operating system, and hardware to achieve your platform's full potential. This guide also teaches database administrators safe and practical ways to scale applications through replication, load balancing, high availability, and failover.Updated to reflect recent advances in cloud- and self-hosted MySQL, InnoDB performance, and new features and tools, this revised edition helps you design a relational data platform that will scale with your business. You'll learn best practices for database security along with hard-earned lessons in both performance and database stability.Dive into MySQL's architecture, including key facts about its storage enginesLearn how server configuration works with your hardware and deployment choicesMake query performance part of your software delivery processExamine enhancements to MySQL's replication and high availabilityCompare different MySQL offerings in managed cloud environmentsExplore MySQL's full stack optimization from application-side configuration to server tuningTurn traditional database management tasks into automated processes
With this unique hands-on guide, you'll learn valuable ways to use Git in many different situations. Raju Gandhi peels back the layers to reveal the simple yet powerful engine that powers Git, with activities that help you truly understand this crucial tool as you get it up and running.
Ready to learn Java? This book combines puzzles, strong visuals, mysteries, and soul-searching interviews with famous Java objects to engage you in many different ways. It's fast, it's fun, and it's effective. And despite its playful appearance, Head First Java is serious stuff: a complete introduction to object-oriented programming and Java.
Author Gaurav Raje shows cloud solution architects and software developers with AWS experience how to build highly secure systems on AWS without increasing overhead.
Even if you're familiar with C# syntax, knowing how to combine various language features is a critical skill when you're building applications. This cookbook is packed full of recipes to help you solve issues for C# programming tasks you're likely to encounter. You'll learn tried-and-true techniques to help you achieve greater productivity and improve the quality of your code.Author and independent consultant Joe Mayo shares some of the most important practices you'll need to be successful as a C# developer. Each section of this cookbook describes some useful facet of the C# programming language. These recipes--the result of many years of experience--are proven concepts for solving real-world problems with C#.Recipes in this book will help you:Set up your project, manage object lifetime, and establish patternsImprove code quality through maintainability, error prevention, and correct syntaxUse LINQ to Objects for in-memory data manipulation and queryingUnderstand the differences between dynamic programming and reflectionApply several async programming features you may not be aware ofWork with data using newer libraries and algorithmsLearn different ways to use new C# features, such as pattern matching and records
Getting started with Arduino is a snap. To use the introductory examples in this guide, all you need is an Arduino Uno or Leonardo, along with a USB cable and an LED. The easy-to-use, free Arduino development environment runs on Mac, Windows, and Linux.
This book introduces the reader to amateur radio and prepares them for the FCC Technician license exam. It focuses on electronics and wireless technologies through projects that provide some hands-on hardware construction and operation.
In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. If you're familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started.
Kubernetes has become an essential part of the daily work for most system, network, and cluster administrators today. But to work effectively together on a production-scale Kubernetes system, they must be able to speak the same language. This book provides a clear guide to the layers of complexity and abstraction that come with running a Kubernetes network.Authors James Strong and Vallery Lancey bring you up to speed on the intricacies that Kubernetes has to offer for large container deployments. If you're to be effective in troubleshooting and maintaining a production cluster, you need to be well versed in the abstraction provided at each layer. This practical book shows you how.Learn the Kubernetes networking modelChoose the best interface for your clusters from the CNCF Container Network Interface projectExplore the networking and Linux primitives that power KubernetesQuickly troubleshoot networking issues and prevent downtimeExamine cloud networking and Kubernetes using the three major providers: Amazon Web Services, Google Cloud, and Microsoft AzureLearn the pros and cons of various network tools--and how to select the best ones for your stack
Features information on vim, the vi clone. This guide helps you learn text editing basics and advanced tools for both editors, such as multi-window editing, how to write both interactive macros and scripts to extend the editor, and power tools for programmers. It also includes an introduction to text editing with vi.
With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance.Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and moreUse automated machine learning to implement a specific subset of use cases with SageMaker AutopilotDive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deploymentTie everything together into a repeatable machine learning operations pipelineExplore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache KafkaLearn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more
Kubernetes has become the dominant container orchestrator, but many organizations that have recently adopted this system are still struggling to run actual production workloads. In this practical book, four software engineers from VMware bring their shared experiences running Kubernetes in production and provide insight on key challenges and best practices.The brilliance of Kubernetes is how configurable and extensible the system is, from pluggable runtimes to storage integrations. For platform engineers, software developers, infosec, network engineers, storage engineers, and others, this book examines how the path to success with Kubernetes involves a variety of technology, pattern, and abstraction considerations.With this book, you will:Understand what the path to production looks like when using KubernetesExamine where gaps exist in your current Kubernetes strategyLearn Kubernetes's essential building blocks--and their trade-offsUnderstand what's involved in making Kubernetes a viable location for applicationsLearn better ways to navigate the cloud native landscape
In today??s IT architectures, microservices and serverless functions play increasingly important roles in process automation. But how do you create meaningful, comprehensive, and connected business solutions when the individual components are decoupled and independent by design? Targeted at developers and architects, this book presents a framework through examples, practical advice, and use cases to help you design and automate complex processes.As systems are more distributed, asynchronous, and reactive, process automation requires state handling to deal with long-running interactions. Author Bernd Ruecker demonstrates how to leverage process automation technology like workflow engines to orchestrate software, humans, decisions, or bots.Learn how modern process automation compares to business process management, service-oriented architecture, batch processing, event streaming, and data pipeline solutionsUnderstand how to use workflow engines and executable process models with BPMNUnderstand the difference between orchestration and choreography and how to balance both
Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to learn by reinforcementand enable a machine to learn by itself.Author Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focus on industrial applications, learnnumerous algorithms, and benefit from dedicated chapters on deploying RL solutions to production. This is no cookbook; doesn't shy away from math and expects familiarity with ML.Learn what RL is and how the algorithms help solve problemsBecome grounded in RL fundamentals including Markov decision processes, dynamic programming, and temporal difference learningDive deep into a range of value and policy gradient methodsApply advanced RL solutions such as meta learning, hierarchical learning, multi-agent, and imitation learningUnderstand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and moreGet practical examples through the accompanying website
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