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.
Get up to speed with Helm, the preeminent package manager for the Kubernetes container orchestration system. This practical guide shows you how to efficiently create, install, and manage the applications running inside your containers. Helm maintainers Matt Butcher, Matt Farina, and Josh Dolitsky explain how this package manager fits into the Kubernetes ecosystem and provide an inside look at Helm's design and best practices.More than 70% of the organizations that work with Kubernetes use Helm today. While the Helm community provides thousands of packages, or charts, to help you get started, this book walks developers and DevOps engineers through the process of creating custom charts to package applications. If you have a working understanding of Kubernetes, you're ready to go.Explore primary features including frequently used Helm commandsLearn how to build and deploy Helm charts from scratchUse Helm to manage complexity and achieve repeatable deploymentsPackage an application and its dependencies for easy installationManage the entire lifecycle of applications on KubernetesExplore ways to extend Helm to add features and functionalityLearn features for testing, handling dependencies, and providing security
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.
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
As data floods into your company, you need to put it to work right away-and SQL is the best tool for the job. With the latest edition of this introductory guide, author Alan Beaulieu helps developers get up to speed with SQL fundamentals for writing database applications, performing administrative tasks, and generating reports.
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.
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.
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.
One key responsibility of product designers and UX practitioners is to conduct formal and informal research to clarify design decisions and business needs. But theres often mystery around product research, with the feeling that you need to be a research Zen master to gather anything useful. Fact is, anyone can conduct product research. With this quick reference guide, youll learn a common language and set of tools to help you carry out research in an informed and productive manner.This book contains four sections, including a brief introduction to UX research, planning and preparation, facilitating research, and analysis and reporting. Each chapter includes a short exercise so you can quickly apply what youve learned.Learn what it takes to ask good research questionsKnow when to use quantitative and qualitative research methodsExplore the logistics and details of coordinating a research sessionUse softer skills to make research seem natural to participantsLearn tools and approaches to uncover meaning in your raw dataCommunicate your findings with a framework and structure
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).
A decade ago, developers built information-sharing software by writing a lot of custom code in a single code base, then adding layers of caching. Now we build information systems: interdependent software and services, data platforms, and event streams. Many of our software-to-systems initiatives fail, though, and when they do, we double down on traditional linear approaches. But linear thinking cannot resolve systems challenges. We need to shift to systems thinking. This book shows software developers and architects how systems thinking can guide you through the emerging complexity of modern systems. Author Diana Montalion presents a vision of technology architecture that transforms how we learn, communicate, and collaborate with others. Through practical examples and scenarios, you'll learn how to develop critical self-reflection and decision-making skills amid complexity and uncertainty--and lead impactful cultural change within your organization. You'll learn: How linear thinking limits your perspective on software systems The obstacles to changing your perspective and how to move past them How systems and nonlinear thinking help you understand and navigate complex issues arising from internal and external factors Methods for creating sound, cross-functional recommendations in the midst of complexity and uncertainty How nonlinear approaches improve the quality of architectural thinking and deliver impactful change for organizations How to provide a modern style of leadership as software becomes information systems
JavaScript gives web developers great power to create rich interactive browser experiences, and much of that power is provided by the browser itself. Modern web APIs enable web-based applications to come to life like never before, supporting actions that once required browser plug-ins. Some are still in an experimental stage, but many are ready for use today. With this hands-on cookbook, author Joe Attardi helps you explore the powerful APIs available in modern browsers and guides you through the specific tasks that they unlock. Because these features are web standards, there is comprehensive documentation available from trusted resources such as MDN Web Docs. The knowledge you'll gain is transferable across different companies and projects. Learn the breadth of functionality available in modern browser APIs Explore future APIs that are still in an experimental stage Discover newer elements, such as dialog that replaces the need for a third-party library Build more powerful and interactive web applications using native APIs Understand the permissions model used by the browser to unlock functionality such as geolocation and push notifications
In today's fast-paced world, more and more organizations require rapid application development with reduced development costs and increased productivity. This practical guide shows application developers how to use PowerApps, Microsoft's no-code/low-code application framework that helps developers speed up development, modernize business processes, and solve tough challenges. Author Arpit Shrivastava provides a comprehensive overview of designing and building cost-effective applications with Microsoft Power Apps. You'll learn fundamental concepts behind low-code and no-code development, how to build applications using pre-built and blank templates, how to design an app using Copilot AI and drag and drop PowerPoint-like controls, use Excel-like expressions to write business logic for an app, and integrate apps with external data sources. With this book, you'll: Learn the importance of no-code/low-code application development Design mobile/tablet (canvas apps) applications using pre-built and blank templates Design web applications (model-driven apps) using low-code, no-code, and pro-code components Integrate PowerApps with external applications Learn basic coding concepts like JavaScript, Power Fx, and C# Apply best practices to customize Dynamics 365 CE applications Dive into Azure DevOps and ALM concepts to automate application deployment Citizen developers and professional application developers alike will be able to design robust applications and solve real world business challenges using Power Apps. Arpit Shrivastava is a Microsoft MVP and Power Platform architect at Capgemini, with vast experience working with Microsoft Dynamics 365 and the Power Platform.
"Python is an excellent way to get started in programming, and this clear, concise guide walks you through Python a step at a time--beginning with basic programming concepts before moving on to functions, data structures, and object-oriented design."--
Keeping up with the Python ecosystem can be daunting. Its developer tooling doesn't provide the out-of-the-box experience native to languages like Rust and Go. When it comes to long-term project maintenance or collaborating with others, every Python project faces the same problem: how to build reliable workflows beyond local development while staying in sync with the evolving ecosystem. With this hands-on guide, Python developers will learn how to forge the moving parts of a Python project into an easy-to-use toolchain, using state-of-the-art tools including Poetry, Nox, pytest, mypy, pre-commit, Black, Ruff, uv, Rye, Hatch, and more. Author Claudio Jolowicz shows you how to create robust Python project structures complete with unit tests, static analysis, code formatting, and type checking. You'll learn how to: Create open source projects with state-of-the-art infrastructure Build a custom infrastructure for all Python projects in a company or team Improve and modernize the infrastructure of an existing Python project Evaluate modern Python tooling for adoption in existing projects Use tools for packaging and dependency management Automate common development tasks such as testing, dependency updates, and publishing releases
How will software development and operations have to change to meet the sustainability and green needs of the planet? And what does that imply for development organizations? In this eye-opening book, sustainable software advocates Anne Currie, Sarah Hsu, and Sara Bergman provide a unique overview of this topic-discussing everything from the likely evolution of national grids to the effect those changes will have on the day-to-day lives of developers. Ideal for everyone from new developers to CTOs, Building Green Software tackles the challenges involved and shows you how to build, host, and operate code in a way that's not only better for the planet, but also cheaper and relatively low-risk for your business. Most hyperscale public cloud providers have already committed to net-zero IT operations by 2030. This book shows you how to get on board.
p>If you thought data structures and algorithms were all just theory, you're missing out on what they can do for your Python code. Learn to use Big O notation to make your code run faster by orders of magnitude. Choose from data structures such as hash tables, trees, and graphs to increase your code's efficiency exponentially. With simple language and clear diagrams, this book makes this complex topic accessible, no matter your background. Every chapter features practice exercises to give you the hands-on information you need to master data structures and algorithms for your day-to-day work. Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. The Python edition uses Python exclusively for all code examples, exercise, and solutions. Use Big O notation to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You'll even encounter a single keyword that can give your code a turbo boost. Practice your new skills with exercises in every chapter, along with detailed solutions. Use these techniques today to make your Python code faster and more scalable.
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