Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. Youll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what youve learned along the way.Youll learn how to:Wrangletransform your datasets into a form convenient for analysisProgramlearn powerful R tools for solving data problems with greater clarity and easeExploreexamine your data, generate hypotheses, and quickly test themModelprovide a low-dimensional summary that captures true "e;signals"e; in your datasetCommunicatelearn R Markdown for integrating prose, code, and results
As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, youll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption.Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed.Examine data management trends, including technological developments, regulatory requirements, and privacy concernsGo deep into the Scaled Architecture and learn how the pieces fit togetherExplore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata
Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems. Practical Data Privacy answers important questions such as: What do privacy regulations like GDPR and CCPA mean for my data workflows and data science use cases? What does "anonymized data" really mean? How do I actually anonymize data? How does federated learning and analysis work? Homomorphic encryption sounds great, but is it ready for use? How do I compare and choose the best privacy-preserving technologies and methods? Are there open-source libraries that can help? How do I ensure that my data science projects are secure by default and private by design? How do I work with governance and infosec teams to implement internal policies appropriately?
If youre a web designer or app developer interested in sophisticated page styling, improved accessibility, and saving time and effort, this book is for you. This revised edition provides a comprehensive guide to CSS implementation, along with a thorough review of the latest CSS specifications.CSS is a constantly evolving language for describing the presentation of web content on screen, printers, speech synthesizers, screen readers, and chat windows. It is used by all browsers on all screen sizes on all types of IoT devices, including phones, computers, video games, televisions, watches, kiosks, and auto consoles. Authors Eric Meyer and Estelle Weyl show you how to improve user experience, speed development, avoid potential bugs, and add life and depth to your applications through layout, transitions and animations, borders, backgrounds, text properties, and many other tools and techniques.This guide covers:Selectors, specificity, and the cascadeValues, units, fonts, and text propertiesPadding, borders, outlines, and marginsColors, backgrounds, and gradientsFloats and positioning tricksFlexible box layoutThe new Grid layout system2D and 3D transforms, transitions, and animationFilters, blending, clipping, and maskingMedia and feature queries
This in-depth book shows you ways to master strategic thinking, manage difficult projects, and set the standard for technical work. You'll learn how to be a leader without direct authority, how to plan ahead so that you're making the right technical decisions, and how to make everyone around you better.
Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively.
This practical book provides a comprehensive overview of troubleshooting and performance tuning best practices for Microsoft SQL Server. Database engineers, including database developers and administrators, will learn how to identify performance issues, troubleshoot the system in a holistic fashion, and properly prioritize tuning efforts to attain the best system performance possible.Author Dmitri Korotkevitch, Microsoft Data Platform MVP and Microsoft Certified Master (MCM), explains the interdependencies between SQL Server database components. You'll learn how to quickly diagnose your system and discover the root cause of any issue. Techniques in this book are compatible with all versions of SQL Server and cover both on-premises and cloud-based SQL Server installations.Discover how performance issues present themselves in SQL ServerLearn about SQL Server diagnostic tools, methods, and technologiesPerform health checks on SQL Server installationsLearn the dependencies between SQL Server componentsTune SQL Server to improve performance and reduce bottlenecksDetect poorly optimized queries and inefficiencies in query execution plansFind inefficient indexes and common database design issuesUse these techniques with Microsoft Azure SQL databases, Azure SQL Managed Instances, and Amazon RDS for SQL Server
With the explosion of data, computing power, and cloud data warehouses, SQL has become an even more indispensable tool for the savvy analyst or data scientist. This practical book reveals new and hidden ways to improve your SQL skills, solve problems, and make the most of SQL as part of your workflow.You'll learn how to use both common and exotic SQL functions such as joins, window functions, subqueries, and regular expressions in new, innovative ways--as well as how to combine SQL techniques to accomplish your goals faster, with understandable code. If you work with SQL databases, this is a must-have reference.Learn the key steps for preparing your data for analysisPerform time series analysis using SQL's date and time manipulationsUse cohort analysis to investigate how groups change over timeUse SQL's powerful functions and operators for text analysisDetect outliers in your data and replace them with alternate valuesEstablish causality using experiment analysis, also known as A/B testing
Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start.You'll discover how to:Apply DevOps best practices to machine learningBuild production machine learning systems and maintain themMonitor, instrument, load-test, and operationalize machine learning systemsChoose the correct MLOps tools for a given machine learning taskRun machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware
What's the answer to today's increasingly complex web applications? Micro-frontends. Inspired by the microservices model, this approach lets you break interfaces into separate features managed by different teams of developers. With this practical guide, Luca Mezzalira shows software architects, tech leads, and software developers how to build and deliver artifacts atomically rather than use a big bang deployment.You'll learn how micro-frontends enable your team to choose any library or framework. This gives your organization technical flexibility and allows you to hire and retain a broad spectrum of talent. Micro-frontends also support distributed or colocated teams more efficiently. Pick up this book and learn how to get started with this technological breakthrough right away.Explore available frontend development architecturesLearn how microservice principles apply to frontend developmentUnderstand the four pillars for creating a successful micro-frontend architectureExamine the benefits and pitfalls of existing micro-frontend architecturesLearn principles and best practices for creating successful automation strategiesDiscover patterns for integrating micro-frontend architectures using microservices or a monolith API layer
This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability.Google engineers Valliappa Lakshmanan, Martin Grner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras.You'll learn how to:Design ML architecture for computer vision tasksSelect a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your taskCreate an end-to-end ML pipeline to train, evaluate, deploy, and explain your modelPreprocess images for data augmentation and to support learnabilityIncorporate explainability and responsible AI best practicesDeploy image models as web services or on edge devicesMonitor and manage ML models
If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous mathematics.
This practical guide presents Lean and Agile principles and patterns to help you move fast at scale - and demonstrates why and how to apply these methodologies throughout your organization, rather than with just one department or team.
This updated book shows your company how to use alignment diagrams to turn valuable customer observations into actionable insight. You'll learn how this unique tool helps you visually map your existing customer experience and envision future solutions.
A new wave of products is helping people change their behavior and daily routines, whether it's exercising more, taking control of their finances, or organizing their email. This practical guide shows you how to design these types of products.
By exploring the fundamental theory behind design choices, this practical guide helps you gain a deeper understanding of Python's implementation. You'll learn how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs
Updated to emphasize new features in Spark 2.4., this second edition shows data engineers and scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine-learning algorithms.
Easy to understand and fun to read, Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3.
Users demand applications that are well behaved, good-looking, and easy to use. This bestselling book captures UI best practices and reusable ideas as design patterns -- solutions to common design problems, tailored to the situation at hand.
Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.
This book will demystify Angular as a framework, as well as provide clear instructions and examples on how to get started with writing scalable Angular applications.
Thinking of migrating to PostgreSQL? This clear, fast-paced introduction helps you understand and use this open source database system. Not only will you learn about the enterprise class features in versions 9.5 to 10, you'll also discover that PostgeSQL is more than a database system-it's an impressive application platform as well.
In order to thoroughly understand what makes Linux tick and why it works so well on a wide variety of systems, you need to delve deep into the heart of the kernel. The kernel handles all interactions between the CPU and the external world, and determines which programs will share processor time, in what order. It manages limited memory so well that hundreds of processes can share the system efficiently, and expertly organizes data transfers so that the CPU isn't kept waiting any longer than necessary for the relatively slow disks.The third edition of Understanding the Linux Kernel takes you on a guided tour of the most significant data structures, algorithms, and programming tricks used in the kernel. Probing beyond superficial features, the authors offer valuable insights to people who want to know how things really work inside their machine. Important Intel-specific features are discussed. Relevant segments of code are dissected line by line. But the book covers more than just the functioning of the code; it explains the theoretical underpinnings of why Linux does things the way it does.This edition of the book covers Version 2.6, which has seen significant changes to nearly every kernel subsystem, particularly in the areas of memory management and block devices. The book focuses on the following topics:Memory management, including file buffering, process swapping, and Direct memory Access (DMA) The Virtual Filesystem layer and the Second and Third Extended FilesystemsProcess creation and schedulingSignals, interrupts, and the essential interfaces to device driversTimingSynchronization within the kernelInterprocess Communication (IPC) Program executionUnderstanding the Linux Kernel will acquaint you with all the inner workings of Linux, but it's more than just an academic exercise. You'll learn what conditions bring out Linux's best performance, and you'll see how it meets the challenge of providing good system response during process scheduling, file access, and memory management in a wide variety of environments. This book will help you make the most of your Linux system.
Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this practical book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs to code-specific systems.
Learn how to get started with Futures Thinking. With this practical guide, Phil Balagtas, founder of the Design Futures Initiative and the global Speculative Futures network, shows you how designers and futurists have made futures work at companies such as Atari, IBM, Apple, Disney, Autodesk, Lufthansa, and McKinsey & Company. This book demystifies the process of Futures Thinking into a language that's practical and useful for both designers and strategists. You'll learn about Strategic Foresight for using ideas about the future to anticipate and prepare for change; explore Speculative Design to deal with the relationship between science, technology, and humans; and Design Fiction to explore and critique possible futures. Balagtas also shares stories from his journey to build a global community and describes how he works with clients to reshape the futures vocabulary. With this guide, you'll learn how to: Prepare your client, team, and/or audience for futures Facilitate and work with the fundamental methods and frameworks Gain advocacy and support within your organization Provide measurable value from the process and outcomes Build a futures culture and team Sustain a culture and support system beyond projects
Frontend developers have to consider many things: browser compatibility, usability, performance, scalability, SEO, and other best practices. But the most fundamental aspect of creating websites is one that often falls short: accessibility. Accessibility is the cornerstone of any website, and if a website is inaccessible, users won't be able to interact with it, obtain information, sign up for services, or buy products. The Web Accessibility Cookbook provides you with dozens of recipes to help you avoid these failures. You'll learn how to build common components, such as main navigation, filters, and dialogs, in an accessible manner. Each recipe not only explains how to build things but also why. Author Manuel Matuzovic provides the knowledge you need to create your own accessible components and address your users' varying needs, abilities, and preferences. With this practical guide, you will: Learn how to build websites that feature inclusive frontends Discover the common obstacles website users face every day Understand how your decisions impact users Learn how to build accessible frontends step-by-step Write high-quality markup and CSS Evaluate the accessibility of frontend components
Geared to intermediate- to advanced-level DBAs and IT professionals looking to enhance their MySQL skills, this guide provides a comprehensive overview on how to manage and optimize MySQL databases. You'll learn how to create databases and implement backup and recovery, security configurations, high availability, scaling techniques, and performance tuning. Using practical techniques, tips, and real-world examples, authors Arunjith Aravindan and Jeyaram Ayyalusamy show you how to deploy and manage MySQL, Amazon RDS, Amazon Aurora, and Azure MySQL. By the end of the book, you'll have the knowledge and skills necessary to administer, manage, and optimize MySQL databases effectively. Design and implement a scalable and reliable database infrastructure using MySQL 8 on premises and cloud Install and configure software, manage user accounts, and optimize database performance Use backup and recovery strategies, security measures, and high availability solutions Apply best practices for database schema design, indexing strategies, and replication techniques Implement advanced database features and techniques such as replication, clustering, load balancing, and high availability Troubleshoot common issues and errors, using diagnostic tools and techniques to identify and resolve problems quickly and efficiently Facilitate major MySQL upgrades including MySQL 5.7 to MySQL 8
Jack the Ripper and legacy codebases have more in common than you'd think. Inspired by forensic psychology methods, you can apply strategies to identify problems in your existing code, assess refactoring direction, and understand how your team influences the software architecture. With its unique blend of criminal psychology and code analysis, Your Code as a Crime Scene arms you with the techniques you need to take on any codebase, no matter what programming language you use.Software development might well be the most challenging task humanity ever attempted. As systems scale up, they also become increasingly complex, expensive to maintain, and difficult to reason about. We can always write more tests, try to refactor, and even fire up a debugger to understand complex coding constructs. That's a great starting point, but you can do so much better.Take inspiration from forensic psychology techniques to understand and improve existing code. Visualize codebases via a geographic profile from commit data to find development hotspots, prioritize technical debt, and uncover hidden dependencies. Get data and develop strategies to make the business case for larger refactorings. Detect and fix organizational problems from the vantage point of the software architecture to remove bottlenecks for the teams.The original Your Code as a Crime Scene from 2014 pioneered techniques for understanding the intersection of people and code. This new edition reflects a decade of additional experience from hundreds of projects. Updated techniques, novel case studies, and extensive new material adds to the strengths of this cult classic.Change how you view software development and join the hunt for better code!What You Need:You need to be comfortable reading code. You also need to use Git (or Subversion, Mercurial or similar version-control tool).
Build interactive, data-driven websites with the potent combination of open-source technologies and web standards, even if you have only basic HTML knowledge. With this popular hands-on guide, youll tackle dynamic web programming with the help of todays core technologies: PHP, MySQL, JavaScript, jQuery, CSS, and HTML5.Explore each technology separately, learn how to use them together, and pick up valuable web programming practices along the way. At the end of the book, youll put everything together to build a fully functional social networking site, using XAMPP or any development stack you choose.Learn PHP in-depth, along with the basics of object-oriented programmingExplore MySQL, from database structure to complex queriesUse the MySQLi Extension, PHPs improved MySQL interfaceCreate dynamic PHP web pages that tailor themselves to the userManage cookies and sessions, and maintain a high level of securityMaster the JavaScript languageand enhance it with jQueryUse Ajax calls for background browser/server communicationAcquire CSS2 and CSS3 skills for professionally styling your web pagesImplement all of the new HTML5 features, including geolocation, audio, video, and the canvas
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