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"With this practical guide, power users and developers will discover ways to resolve everyday challenges by building end-to-end solutions with the Microsoft Power Platform. Author Jason Rivera, who specializes in SharePoint and the Microsoft 365 solution architecture, provides a comprehensive overview of how to use the Power Platform to build end-to-end solutions that address tactical business needs. By learning key components of the platform, including Power Apps, Power Automate, and Power BI, you'll be able to build low-code and no code applications, automate repeatable business processes, and create interactive reports from available data"--

"Cybersecurity is broken. Year after year, attackers remain unchallenged and undeterred, while engineering teams feel pressure to design, build, and operate 'secure' systems. Failure can't be prevented, mental models of systems are incomplete, and our digital world constantly evolves. How can we verify that our systems behave the way we expect? What can we do to improve our systems' resilience? In this comprehensive guide, authors Kelly Shortridge and Aaron Rinehart help you navigate the challenges of sustaining resilience in complex software systems by using the principles and practices of security chaos engineering. By preparing for adverse events, you can ensure they don't disrupt your ability to innovate, move quickly, and achieve your engineering and business goals"--Back cover.

"Learn how to build end-to-end scalable machine learning solutions with Apache Spark. With this practical guide, author Adi Polak introduces data and ML practitioners to creative solutions that supersede today's traditional methods. You'll learn a more holistic approach that takes you beyond specific requirements and organizational goals--allowing data and ML practitioners to collaborate and understand each other better ... [Also] examines several technologies for building end-to-end distributed ML workflows based on the Apache Spark ecosystem with Spark MLlib, MLflow, TensorFlow, and PyTorch"--

"The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI--a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public."--

This practical guide shows data scientists, data engineers, architects, and business analysts how to get started with a graph database using TigerGraph, one of the leading graph database models available.

Improve the user experience for your Rails app with rich, engaging client-side interactions. Learn to use the Rails 7 tools and simplify the complex JavaScript ecosystem. It's easier than ever to build user interactions with Hotwire, Turbo, and Stimulus. You can add great front-end flair without much extra complication. Use React to build a more complex set of client-side features. Structure your code for different levels of client-side needs with these powerful options. Add to your toolkit today!It's hard to have a Rails application without integrating some client-side logic. But client-side coding tools, and the Rails tools for integrating with them, all change continuously. Rails 7 simplifies client-side integration with the Hotwire gem. It's a great way to build client interaction with server-side HTML and a small amount of JavaScript.In the latest edition of this book, learn how to use Rails 7 and its front-end bundling tools to build rich front-end logic into your Rails applications. The job is even easier with Stimulus, a library that brings Rails conventions to JavaScript tools. And you can also add in React, a larger framework that automatically updates the browser when your data changes.Learn the basics of Turbo, Stimulus, and TypeScript, and add pizazz to your application. Structure your web application to best manage your state. Learn how to interact with data on the server while still keeping the user experience interactive. Use the type system in TypeScript to expand on JavaScript and help prevent error conditions. Debug and test your front-end application with tools specific to each framework.There are a lot of ways to do client-side coding, and Rails is here to help.What You Need:This book requires Ruby on Rails 7.0 or later, React 17.0.0 or later. Other dependencies will be added by Rails.

Data has become the most powerful tool in business today, and telling its story effectively is critical. Yet one of the best communicatorscoloris the most neglected tool in data visualization. With this book, DATAcated founder Kate Strachnyi provides the ultimate guide to the correct use of color for representing data in graphs, charts, tables, and infographics.Ideal for data and business analysts, data scientists, and others who design infographics and data visualizations, this practical resource explores color tips and tricks, including the theories behind them and why they work the way they do. ColorWise covers the psychology, history, and culture of many different colors. This book is also a useful teaching tool for learning about proper use of color for data storytelling techniques and dashboarding.You'll explore:The role that color theory plays in data visualization and storytellingVarious color techniques you can use to improve data visualizationsHow colors affect your audience's understanding of data visualizationsHow to use color intentionally to help guide your audienceTips for using colors that people with color vision deficiency can interpretHow to apply the book's guidelines for use in your own projects

With millions of new users and several new models, the Raspberry Pi ecosystem continues to expandalong with a lot of new questions about the Pis capabilities. The second edition of this popular cookbook provides more than 240 hands-on recipes for running this tiny low-cost computer with Linux, programming it with Python, and hooking up sensors, motors, and other hardwareincluding Arduino and the Internet of Things.Prolific hacker and author Simon Monk also teaches basic principles to help you use new technologies with Raspberry Pi as its ecosystem continues to develop. This cookbook is ideal for programmers and hobbyists familiar with the Pi through resources, including Getting Started with Raspberry Pi (OReilly). Python and other code examples from the book are available on GitHub.Set up your Raspberry Pi and connect to a networkWork with its Linux-based operating systemProgram Raspberry Pi with PythonGive your Pi "e;eyes"e; with computer visionControl hardware through the GPIO connectorUse Raspberry Pi to run different types of motorsWork with switches, keypads, and other digital inputsUse sensors to measure temperature, light, and distanceConnect to IoT devices in various waysCreate dynamic projects with Arduino

Perform fast interactive analytics against different data sources using the Trino high-performance distributed SQL query engine. With this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's Hive, Cassandra, a relational database, or a proprietary data store. Analysts, software engineers, and production engineers will learn how to manage, use, and even develop with Trino.Initially developed by Facebook, open source Trino is now used by Netflix, Airbnb, LinkedIn, Twitter, Uber, and many other companies. Matt Fuller, Manfred Moser, and Martin Traverso show you how a single Trino query can combine data from multiple sources to allow for analytics across your entire organization.Get started: Explore Trino's use cases and learn about tools that will help you connect to Trino and query dataGo deeper: Learn Trino's internal workings, including how to connect to and query data sources with support for SQL statements, operators, functions, and morePut Trino in production: Secure Trino, monitor workloads, tune queries, and connect more applications; learn how other organizations apply Trino

Is Kubernetes ready for stateful workloads? This open source system has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help.Using Kubernetes as your platform, you'll learn open source technologies that are designed and built for the cloud. Authors Jeff Carpenter and Patrick McFadin provide case studies to help you explore new use cases and avoid the pitfalls others have faced. Youll get an insider's view of what's coming from innovators who are creating next-generation architectures and infrastructure.With this book, you will:Learn how to use basic Kubernetes resources to compose data infrastructureAutomate the deployment and operations of data infrastructure on Kubernetes using tools like Helm and operatorsEvaluate and select data infrastructure technologies for use in your applicationsIntegrate data infrastructure technologies into your overall stackExplore emerging technologies that will enhance your Kubernetes-based applications in the future

The low cost of getting started with cloud services can easily evolve into a significant expense down the road. That's challenging for teams developing data pipelines, particularly when rapid changes in technology and workload require a constant cycle of redesign. How do you deliver scalable, highly available products while keeping costs in check? With this practical guide, author Sev Leonard provides a holistic approach to designing scalable data pipelines in the cloud. Intermediate data engineers, software developers, and architects will learn how to navigate cost/performance trade-offs and how to choose and configure compute and storage. You'll also pick up best practices for code development, testing, and monitoring. By focusing on the entire design process, you'll be able to deliver cost-effective, high-quality products. This book helps you: Reduce cloud spend with lower cost cloud service offerings and smart design strategies Minimize waste without sacrificing performance by rightsizing compute resources Drive pipeline evolution, head off performance issues, and quickly debug with effective monitoring Set up development and test environments that minimize cloud service dependencies Create data pipeline code bases that are testable and extensible, fostering rapid development and evolution Improve data quality and pipeline operation through validation and testing

"Learn the core concepts of Vue.js, the modern JavaScript framework for building frontend applications and interfaces from scratch. With concise, practical, and clear examples, this book takes web developers step-by-step through the tools and libraries in the Vue.js ecosystem and shows them how to create complete applications for real-world web projects. You'll learn how to handle data communication between components with Pinia architecture, develop a manageable routing system for a frontend project to control the application flow, and produce basic animation effects to create a better user experience"--

After decades of relative obscurity, functional programming is finally coming into its own. With concise, easy-to-read code that supports asynchronous, concurrent processing, aspects of functional programming have begun to appear in several traditionally object-oriented languages such as C# and Java. This practical book shows C# programmers how to use functional programming features without having to navigate an entirely new language. Because of the shared runtime environment common to C# and F# languages, it's possible to use most of F#'s functional features in C# as well. Author Simon J. Painter explains how you can write functional code in C# right away, without having to install dependencies or features newer than .NET 3. You'll learn why functional programming concepts can bring immediate benefit to your work. Learn what functional programming is and how it originated Discover features of the functional paradigm using a more familiar language Start coding functionally in C# right away, without relying on third-party libraries Write code that's more robust, less error prone, and easier to test Examine less conventional ways to look at structures available in C# Explore the practicalities of using functional C# in a business environment.

Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitation techniques. This practical book explains how differential privacy (DP) can help. Authors Ethan Cowan, Michael Shoemate, and Mayana Pereira explain how these techniques enable data scientists, researchers, and programmers to run statistical analyses that hide the contribution of any single individual. You'll dive into basic DP concepts and understand how to use open source tools to create differentially private statistics, explore how to assess the utility/privacy trade-offs, and learn how to integrate differential privacy into workflows. With this book, you'll learn: How DP guarantees privacy when other data anonymization methods don't What preserving individual privacy in a dataset entails How to apply DP in several real-world scenarios and datasets Potential privacy attack methods, including what it means to perform a reidentification attack How to use the OpenDP library in privacy-preserving data releases How to interpret guarantees provided by specific DP data releases

If your organization plans to modernize services and move to the cloud from legacy software or a private cloud on premises, this book is for you. Software developers, solution architects, cloud engineers, and anybody interested in cloud technologies will learn fundamental concepts for cloud computing, migration, transformation, and development using Microsoft Azure. Author and Microsoft MVP Jonah Carrio Andersson guides you through cloud computing concepts and deployment models, the wide range of modern cloud technologies, application development with Azure, team collaboration services, security services, and cloud migration options in Microsoft Azure. You'll gain insight into the Microsoft Azure cloud services that you can apply in different business use cases, software development projects, and modern solutions in the cloud. You'll also become fluent with Azure cloud migration services, serverless computing technologies that help your development team work productively, Azure IoT, and Azure cognitive services that make your application smarter. This book also provides real-world advice and best practices based on the author's own Azure migration experience.

"As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. [This] is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the 'technical/nontechnical' divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas"--

The perimeter defenses guarding your network perhaps are not as secure as you think. Hosts behind the firewall have no defenses of their own, so when a host in the "e;trusted"e; zone is breached, access to your data center is not far behind. Thats an all-too-familiar scenario today. With this practical book, youll learn the principles behind zero trust architecture, along with details necessary to implement it.The Zero Trust Model treats all hosts as if theyre internet-facing, and considers the entire network to be compromised and hostile. By taking this approach, youll focus on building strong authentication, authorization, and encryption throughout, while providing compartmentalized access and better operational agility.Understand how perimeter-based defenses have evolved to become the broken model we use todayExplore two case studies of zero trust in production networks on the client side (Google) and on the server side (PagerDuty)Get example configuration for open source tools that you can use to build a zero trust networkLearn how to migrate from a perimeter-based network to a zero trust network in production

"When Isaac Newton developed calculus in the 1600s, he was trying to tie together math and physics in an intuitive, geometrical way. But over time math and physics teaching became heavily weighted toward algebra, and less toward geometrical problem solving. However, many practicing mathematicians and physicists will get their intuition geometrically first and do the algebra later. Make:Calculus imagines how Newton might have used 3D printed models, construction toys, programming, craft materials, and an Arduino or two to teach calculus concepts in an intuitive way. The book uses as little reliance on algebra as possible while still retaining enough to allow comparison with a traditional curriculum. This book is not a traditional Calculus I textbook. Rather, it will take the reader on a tour of key concepts in calculus that lend themselves to hands-on projects. This book also defines terms and common symbols for them so that self-learners can learn more on their own"

Edge AI is transforming the way computers interact with the real world, allowing IoT devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. With techniques like embedded machine learning, developers can capture human intuition and deploy it to any target--from ultra-low power microcontrollers to embedded Linux devices. This practical guide gives engineering professionals, including product managers and technology leaders, an end-to-end framework for solving real-world industrial, commercial, and scientific problems with edge AI. You'll explore every stage of the process, from data collection to model optimization to tuning and testing, as you learn how to design and support edge AI and embedded ML products. Edge AI is destined to become a standard tool for systems engineers. This high-level road map helps you get started. Develop your expertise in AI and ML for edge devices Understand which projects are best solved with edge AI Explore key design patterns for edge AI apps Learn an iterative workflow for developing AI systems Build a team with the skills to solve real-world problems Follow a responsible AI process to create effective products

Why are so many companies adopting GitOps for their DevOps and cloud native strategy? This reliable framework is quickly becoming the standard method for deploying apps to Kubernetes. With this practical, developer-oriented book, DevOps engineers, developers, IT architects, and SREs will learn the most useful recipes and examples for following GitOps practices.

The software development ecosystem is constantly changing, providing a constant stream of new tools, frameworks, techniques, and paradigms. Over the past few years, incremental developments in core engineering practices for software development have created the foundations for rethinking how architecture changes over time, along with ways to protect important architectural characteristics as it evolves. This practical guide ties those parts together with a new way to think about architecture and time.

While many introductory guides to AI are calculus books in disguise, this one mostly eschews the math. Instead, author Jeff Prosise helps engineers and software developers build an intuitive understanding of AI to solve business problems. Need to create a system to detect the sounds of illegal logging in the rainforest, analyze text for sentiment, or predict early failures in rotating machinery? This practical book teaches you the skills necessary to put AI and machine learning to work at your company.Applied Machine Learning and AI for Engineers provides examples and illustrations from the AI and ML course Prosise teaches at companies and research institutions worldwide. There's no fluff and no scary equationsjust a fast start for engineers and software developers, complete with hands-on examples.This book helps you:Learn what machine learning and deep learning are and what they can accomplishUnderstand how popular learning algorithms work and when to apply themBuild machine learning models in Python with Scikit-Learn, and neural networks with Keras and TensorFlowTrain and score regression models and binary and multiclass classification modelsBuild facial recognition models and object detection modelsBuild language models that respond to natural-language queries and translate text to other languagesUse Cognitive Services to infuse AI into the apps that you write

Expert advice on C programming is hard to find. While much help is available for object-oriented programming languages, there's surprisingly little for the C language. With this hands-on guide, beginners and experienced C programmers alike will find guidance about design decisions, including how to apply them bit by bit to running code examples when building large-scale programs.Christopher Preschern, a leading member of the design patterns community, answers questions such as how to structure C programs, cope with error handling, or design flexible interfaces. Whether you're looking for one particular pattern or an overview of design options for a specific topic, this book shows you how to implement hands-on design knowledge specifically for the C programming language.You'll find design patterns for:Error handlingReturning error informationMemory managementReturning data from C functionsData lifetime and ownershipFlexible APIsFlexible iterator interfacesOrganizing files in modular programsEscaping #ifdef Hell

Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library.Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve.Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answeringLearn how transformers can be used for cross-lingual transfer learningApply transformers in real-world scenarios where labeled data is scarceMake transformer models efficient for deployment using techniques such as distillation, pruning, and quantizationTrain transformers from scratch and learn how to scale to multiple GPUs and distributed environments

Candlesticks have become a key component of platforms and charting programs for financial trading. With these charts, traders can learn underlying patterns for interpreting price action history and forecasts. This A-Z guide shows portfolio managers, quants, strategists, and analysts how to use Python to recognize, scan, trade, and back-test the profitability of candlestick patterns.Financial author, trading consultant, and institutional market strategist Sofien Kaabar shows you how to create a candlestick scanner and indicator so you can compare the profitability of these patterns. With this hands-on book, you'll also explore a new type of charting system similar to candlesticks, as well as new patterns that have never been presented before.With this book, you will:Create and understand the conditions required for classic and modern candlestick patternsLearn the market psychology behind themUse a framework to learn how back-testing trading strategies are conductedExplore different charting systems and understand their limitationsImport OHLC historical FX data in Python in different time framesUse algorithms to scan for and reproduce patternsLearn a pattern's potential by evaluating its profitability and predictability