Bücher veröffentlicht von O'Reilly Media

Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you'll also gain practical insights into the state of data science and how to use those insights to maximize your career.Learn how to:Use Python code and libraries like SymPy, NumPy, and scikit-learn to explore essential mathematical concepts like calculus, linear algebra, statistics, and machine learningUnderstand techniques like linear regression, logistic regression, and neural networks in plain English, with minimal mathematical notation and jargonPerform descriptive statistics and hypothesis testing on a dataset to interpret p-values and statistical significanceManipulate vectors and matrices and perform matrix decompositionIntegrate and build upon incremental knowledge of calculus, probability, statistics, and linear algebra, and apply it to regression models including neural networksNavigate practically through a data science career and avoid common pitfalls, assumptions, and biases while tuning your skill set to stand out in the job market

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You'll understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, and governance that are critical in any data environment regardless of the underlying technology.This book will help you:Get a concise overview of the entire data engineering landscapeAssess data engineering problems using an end-to-end framework of best practicesCut through marketing hype when choosing data technologies, architecture, and processesUse the data engineering lifecycle to design and build a robust architectureIncorporate data governance and security across the data engineering lifecycle

This guide teaches Rust using a single small, complete, focused program in each chapter. Author Ken Youens-Clark shows you how to start, write, and test each of these programs to create a finished product. You'll learn how to handle errors in Rust, read and write files, and use regular expressions, Rust types, structs, and more.

If you use SQL in your day-to-day work as a data analyst, data scientist, or data engineer, this popular pocket guide is your ideal on-the-job reference. You'll find many examples that address the language's complexities, along with key aspects of SQL used in Microsoft SQL Server, MySQL, Oracle Database, PostgreSQL, and SQLite.In this updated edition, author Alice Zhao describes how these database management systems implement SQL syntax for both querying and making changes to a database. You'll find details on data types and conversions, regular expression syntax, window functions, pivoting and unpivoting, and more.Quickly look up how to perform specific tasks using SQLApply the book's syntax examples to your own queriesUpdate SQL queries to work in five different database management systems NEW: Connect Python and R to a relational databaseNEW: Look up frequently asked SQL questions in the "e;How Do I?"e; chapter

Learn how to use Autodesk Fusion 360 to digitally model your own original projects for a 3D printer or a CNC device.

How do you use PowerShell to navigate the filesystem, manage files and folders, or retrieve a web page? This introduction to the PowerShell language and scripting environment provides more than 400 task-oriented recipes to help you solve all kinds of problems. Intermediate to advanced system administrators will find more than 100 tried-and-tested scripts they can copy and use immediately.Updated for PowerShell 5.1 and Open Source PowerShell up to 7.0 and beyond, this comprehensive cookbook includes hands-on recipes for common tasks and administrative jobs that you can apply whether you're on the client or server version of Windows. You also get quick references to technologies used in conjunction with PowerShell, including regular expressions, the XPath language, format specifiers, and frequently referenced .NET, COM, and WMI classes.Learn how to use PowerShell on Windows 10 and Windows Server 2019Tour PowerShell's core features, including the command model, object-based pipeline, and ubiquitous scriptingMaster fundamentals such as the interactive shell, pipeline, and object conceptsPerform common tasks that involve working with files, internet-connected scripts, user interaction, and moreSolve tasks in systems and enterprise management, such as working with Active Directory and the filesystem

Written by two experienced systems programmers, this book explains how Rust manages to bridge the gap between performance and safety, and how you can take advantage of it.

Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading.You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field.Set up a proper Python environment for algorithmic tradingLearn how to retrieve financial data from public and proprietary data sourcesExplore vectorization for financial analytics with NumPy and pandasMaster vectorized backtesting of different algorithmic trading strategiesGenerate market predictions by using machine learning and deep learningTackle real-time processing of streaming data with socket programming toolsImplement automated algorithmic trading strategies with the OANDA and FXCM trading platforms

Your team will change whether you like it or not. People will come and go. Your company might double in size or even be acquired. In this practical book, author Heidi Helfand shares techniques for reteaming effectively. Engineering leaders will learn how to catalyze team change to reduce the risk of attrition, learning and career stagnation, and the development of knowledge silos.Based on research into well-known software companies, the patterns in this book help CTOs and team managers effectively integrate new hires into an existing team, manage a team that has lost members, or deal with unexpected change. Youll learn how to isolate teams for focused innovation, rotate team members for knowledge sharing, break through organizational apathy, and more.Youll explore:Real-world examples that demonstrate why and how organizations reteamFive reteaming patterns: One by One, Grow and Split, Isolation, Merging, and SwitchingTactics to help you master dynamic reteaming in your companyStories that demonstrate problems caused by reteaming anti-patterns

With this practical guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexity.

This is a first-principles-based, practical introduction to the fundamentals of data science aimed at the mathematically-comfortable reader with some programming skills.

Google's Site Reliability Engineering book ignited an industry discussion on what it means to run production services today. Now, Google engineers who worked on that bestseller introduce The Site Reliability Workbook, a hands-on companion that uses concrete examples to show you how to put SRE principles and practices to work in your environment.

User experience doesn't happen on a screen; it happens in the mind, and the experience is multidimensional and multisensory. This practical book will help you uncover critical insights about how your customers think so you can create products or services with an exceptional experience.

In todays lightning-fast technology world, good product management is critical to maintaining a competitive advantage. Yet, managing human beings and navigating complex product roadmaps is no easy task, and its rare to find a product leader who can steward a digital product from concept to launch without a couple of major hiccups. Why do some product leaders succeed while others dont?This insightful book presents interviews with nearly 100 leading product managers from all over the world. Authors Richard Banfield, Martin Eriksson, and Nate Walkingshaw draw on decades of experience in product design and development to capture the approaches, styles, insights, and techniques of successful product managers. If you want to understand what drives good product leaders, this book is an irreplaceable resource.In three parts, Product Leadership helps you explore:Themes and patterns of successful teams and their leaders, and ways to attain those characteristicsBest approaches for guiding your product team through the startup, emerging, and enterprise stages of a companys evolutionStrategies and tactics for working with customers, agencies, partners, and external stakeholders

This cookbook is perfect for anyone who wants to experiment with the popular Arduino microcontroller and programming environment. Updated for Arduino 1.8, the third edition includes more than 200 tips and techniques for building a variety of objects and prototypes

Updated for both Python 3.4 and 2.7, this convenient pocket guide is the perfect on-the-job quick reference. Youll find concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python tools. The handy index lets you pinpoint exactly what you need.Written by Mark Lutzwidely recognized as the worlds leading Python trainerPython Pocket Reference is an ideal companion to OReillys classic Python tutorials, Learning Python and Programming Python, also written by Mark.This fifth edition covers:Built-in object types, including numbers, lists, dictionaries, and moreStatements and syntax for creating and processing objectsFunctions and modules for structuring and reusing codePythons object-oriented programming toolsBuilt-in functions, exceptions, and attributesSpecial operator overloading methodsWidely used standard library modules and extensionsCommand-line options and development toolsPython idioms and hintsThe Python SQL Database API

Go is rapidly becoming the preferred language for building web services. While there are plenty of tutorials available that teach Go's syntax to developers with experience in other programming languages, tutorials aren't enough. They don't teach Go's idioms, so developers end up recreating patterns that don't make sense in a Go context. This practical guide provides the essential background you need to write clear and idiomatic Go.No matter your level of experience, you'll learn how to think like a Go developer. Author Jon Bodner introduces the design patterns experienced Go developers have adopted and explores the rationale for using them. You'll also get a preview of Go's upcoming generics support and how it fits into the language.Learn how to write idiomatic code in Go and design a Go projectUnderstand the reasons for the design decisions in GoSet up a Go development environment for a solo developer or teamLearn how and when to use reflection, unsafe, and cgoDiscover how Go's features allow the language to run efficientlyKnow which Go features you should use sparingly or not at all

"When you have questions about C# 12 or .NET 8, this best-selling guide has the answers you need. C# is a language of unusual flexibility and breadth, and with its continual growth, there's always so much more to learn. In the tradition of O'Reilly's Nutshell guides, this thoroughly updated edition is simply the best one-volume reference to the C# language available today."--Page [4] of cover.

"Messy code is a nuisance. 'Tidying' code, to make it more readable, requires breaking it up into manageable sections. In this practical guide, author Kent Beck, creator of Extreme Programming and pioneer of software patterns, suggests when and where you might apply tidyings to improve your code while keeping the overall structure of the system in mind. Instead of trying to master tidying all at once, this book lets you try out a few examples that make sense for your problem. If you have a big function containing many lines of code, you'll learn how to logically divide it into smaller chunks. Along the way, you'll learn the theory behind software design: coupling, cohesion, discounted cash flows, and optionality."--Provided by publisher.

Product management naturally incorporates empathy, psychology, and thinking outside the box in pursuit of the best design for products. But how often do you apply those same skills to your relationships with people in your company? By breaking the art of stakeholder management into simple lessons and frameworks, this practical book shows product managers how to manage the crucial relationships that will help you make an impact and advance your career. You'll learn how to build trusting relationships with stakeholders, optimize your communication for different audiences, get buy-in for your ideas and roadmaps, and have stakeholders appreciate it when you say no. You'll learn how to: Build and maintain trust with your stakeholders Map your organization and identify the real power players Establish roles and build an extended team that works well together Communicate in a way that speaks to the needs and goals of different stakeholders Get buy-in on your ideas and roadmap Make stakeholders appreciate and support you when you say "no" Sustain buy-in over time Manage difficult stakeholders and personalities

In this book, author Matheus Facure explains the untapped potential of causal inference for estimating impacts and effects.

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?

With Learning JavaScript Design Patterns, youll learn how to write beautiful, structured, and maintainable JavaScript by applying classical and modern design patterns to the language. If you want to keep your code efficient, more manageable, and up-to-date with the latest best practices, this book is for you.Explore many popular design patterns, including Modules, Observers, Facades, and Mediators. Learn how modern architectural patternssuch as MVC, MVP, and MVVMare useful from the perspective of a modern web application developer. This book also walks experienced JavaScript developers through modern module formats, how to namespace code effectively, and other essential topics.Learn the structure of design patterns and how they are writtenUnderstand different pattern categories, including creational, structural, and behavioralWalk through more than 20 classical and modern design patterns in JavaScriptUse several options for writing modular codeincluding the Module pattern, Asyncronous Module Definition (AMD), and CommonJSDiscover design patterns implemented in the jQuery libraryLearn popular design patterns for writing maintainable jQuery plug-ins"e;This book should be in every JavaScript developers hands. Its the go-to book on JavaScript patterns that will be read and referenced many times in the future."e;Andre Hansson, Lead Front-End Developer, presis!

Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, youll quickly grasp Pythons fundamentals, working with the built-in data structures and functions. Then youll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If youre intrigued by what you can do with context managers, decorators, comprehensions, and generators, its all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time.Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.

Get up to speed on Git for tracking, branching, merging, and managing code revisions. Through a series of step-by-step tutorials, this practical guide takes you quickly from Git fundamentals to advanced techniques, and provides friendly yet rigorous advice for navigating the many functions of this open source version control system.This thoroughly revised edition also includes tips for manipulating trees, extended coverage of the reflog and stash, and a complete introduction to the GitHub repository. Git lets you manage code development in a virtually endless variety of ways, once you understand how to harness the systems flexibility. This book shows you how.Learn how to use Git for several real-world development scenariosGain insight into Gits common-use cases, initial tasks, and basic functionsUse the system for both centralized and distributed version controlLearn how to manage merges, conflicts, patches, and diffsApply advanced techniques such as rebasing, hooks, and ways to handle submodulesInteract with Subversion (SVN) repositoriesincluding SVN to Git conversionsNavigate, use, and contribute to open source projects though GitHub

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.

Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work.RStudio engineers Max Kuhn and Julia Silge demonstrate ways to create models by focusing on an R dialect called the tidyverse. Software that adopts tidyverse principles shares both a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. You'll understand why the tidymodels framework has been built to be used by a broad range of people.With this book, you will:Learn the steps necessary to build a model from beginning to endUnderstand how to use different modeling and feature engineering approaches fluentlyExamine the options for avoiding common pitfalls of modeling, such as overfittingLearn practical methods to prepare your data for modelingTune models for optimal performanceUse good statistical practices to compare, evaluate, and choose among models

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.