Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce, Andrew Bruce English | ISBN: 1491952962 | 2016 A key component of data science is statistics and machine learning, but only a small proportion of data scientists are actually trained as statisticians. This concise guide illustrates how to apply statistical concepts essential to data science, with advice on how to avoid their misuse. Many courses and books teach basic statistics, but rarely from a data science perspective. And while many data science resources incorporate statistical methods, they typically lack a deep statistical perspective. This quick reference book bridges that gap in an accessible, readable format.
2024-05-17 09:38:25 3.16MB Statistics Data Scientists
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Practical Statistics for Data Scientists 50 Essential Concepts 英文epub 本资源转载自网络,如有侵权,请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书
2022-05-05 23:31:13 12.58MB Practical Statistics Data Scientists
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解释器仪表板 创建人:Oege Dijk 该软件包使快速部署仪表板Web应用程序变得很方便,该应用程序说明了(兼容scikit-learn的)机器学习模型的工作原理。 仪表板提供有关模型性能,特征重要性,特征对单个预测的贡献,“假设条件”分析,部分依赖图,SHAP(交互作用)值,单个决策树的可视化等交互式图表。 您还可以在笔记本/便携式计算机环境中以交互方式浏览仪表板的组件(或直接从那里启动仪表板)。 或使用自己的和说明设计仪表板(由于库的模块化设计)。 您可以将多个仪表板组合到一个。 例如部署在: ,在详细的文档 ,例如如何推出针对不同型号笔记本的仪表板,以及如何与解释器对象交互的例子笔记本电脑。 与scikit-learn , xgboost , catboost , lightgbm等一起使用。 安装 您可以通过pip安装该软件包: pip install explain
2022-04-18 18:08:30 57.34MB dashboard plotly dash data-scientists
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Practical Statistics for Data Scientists 50 Essential Concepts 英文无水印转化版pdf pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络,如有侵权,请联系上传者或csdn删除查看此书详细信息请在美国亚马逊官网搜索此书
Practical statistics for data scientistsby peter bruce and andrew bruceCopyright@ 2017 Peter Bruce and Andrew Bruce. All rights reservedPrinted in the united states of americaPublished by o'reilly media, InC. 1005 Gravenstein Highway North,Sebastopol, Ca95472O'Reilly books may be purchased for educational, business, or sales promotionaluse.onlineeditionsarealsoavailableformosttitles(http:/oreilly.com/safari)For more information, contact our corporate/institutional sales department: 800998-9938 or corporateoreilly com■ editor: Shannon cuttProduction editor. Kristen brownCopyeditor: Rachel monaghana Proofreader eliahu sussmana Indexer Ellen Troutman-Zaiga Interior Designer: David FutatoCover Designer: Karen Montgomeryllustrator. rebecca demaresta May 2017: First EditionRevision history for the First edition2017-05-09 First releaseSeehttp://oreilly.com/catalog/errata.csp?isbn=9781491952962forreleasedetailsThe o reilly logo is a registered trademark of o' reilly media, Inc. PracticalStatistics for Data Scientists, the cover image, and related trade dress aretrademarks of o'Reilly Media, IncWhile the publisher and the authors have used good faith efforts to ensure that theinformation and instructions contained in this work are accurate, the publisher andthe authors disclaim all responsibility for errors or omissions, including withoutlimitation responsibility for damages resulting from the use of or reliance on thiswork. Use of the information and instructions contained in this work is at yourown risk. If any code samples or other technology this work contains or describesis subject to open source licenses or the intellectual property rights of others, it isyour responsibility to ensure that your use thereof complies with such licensesand/or rights978-1-491-95296-2DedicationWe would like to dedicate this book to the memories of our parents Victor gBruce and Nancy C. bruce, who cultivated a passion for math and science and toour early mentors John W. Tukey and Julian Simon, and our lifelong friend GeoffWatson, who helped inspire us to pursue a career in statisticsPrefaceThis book is aimed at the data scientist with some familiarity with the rprogramming language, and with some prior(perhaps spotty or ephemeral)exposure to statistics. Both of us came to the world of data science from the worldof statistics, so we have some appreciation of the contribution that statistics canmake to the art of data science. at the same time we are well aware of thelimitations of traditional statistics instruction: statistics as a discipline is a centuryand a half old and most statistics textbooks and courses are laden with themomentum and inertia of an ocean linerTwo goals underlie this bookTo lay out, in digestible, navigable, and easily referenced form, key conceptsfrom statistics that are relevant to data scienceTo explain which concepts are important and useful from a data scienceperspective, which are less so, and whyWhat to ExpectKEY TERMSData science is a fusion of multiple disciplines, inc hiding statistics, computer science, informationtechnology, and domain-specific fields. As a result, several different terms could be used to reference aiven concept. Key terms and their synonyms will be highlighted throughout the book n a side bar such asConventions used in This bookThe following typographical conventions are used in this bookItalicIndicates new terms URls. email addresses filenames and file extensionsConstant widthUsed for program listings, as well as within paragraphs to refer to programelements such as variable or function names, databases, data types,environment variables, statements, and keywordsConstant width boldShows commands or other text that should be typed literally by the userConstant width italicShows text that should be replaced with user-supplied values or by valuesdetermined by contextTIPThis element signifies a tip or suggestionNOTEThis element signifies a general noteWARNINGThis element indicates a warning or cautionUsing Code ExamplesSupplemental material(code examples, exercises, etc. is available for downloadathttps://github.com/andrewgbruce/statistics-for-data-scientistsThis book is here to help you get your job done. In general, if example code isoffered with this book, you may use it in your programs and documentation. youdo not need to contact us for permission unless you're reproducing a significantportion of the code. For example, writing a program that uses several chunks ofcode from this book does not require permission. Selling or distributing a CD-ROM of examples from O Reilly books does require permission. answering aquestion by citing this book and quoting example code does not requirepermission. Incorporating a significant amount of example code from this bookinto your product's documentation does require permissionWe appreciate, but do not require, attribution. An attribution usually includes thetitle, author, publisher, and isBN. For example: Practical Statistics for dataScientists by Peter Bruce and Andrew Bruce(o'Reilly). Copyright 2017 PeterBruce and andrew bruce. 978-1-491-95296-2If you feel your use of code examples falls outside fair use or the permission givenabove,feelfreetocontactusatpermissions(@oreilly.comSafari( Books onlineNOTESafari books Online is an on-demand digital library that delivers expert contentin both book and video form from the worlds leading authors in technology andbusinessTechnology professionals, software developers, web designers, and business andcreative professionals use Safari Books Online as their primary resource forresearch, problem solving, learning, and certification trainingSafari Books Online offers a range of plans and pricing for enterprise,government, education, and individualsMembers have access to thousands of books, training videos, and prepublicationmanuscripts in one fully searchable database from publishers like O'ReillyMedia, Prentice Hall Professional, Addison-Wesley Professional, MicrosoftPress, Sams, Que, Peachpit Press, Focal Press, Cisco PreSs, John Wiley sonsSyngress, Morgan Kaufmann, IBM Redbooks, Packt, Adobe Press, FT Press,press, Manning, New riders, McGraw-Hill, Jones bartlett, CourseTechnology, and hundreds more. 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2019-12-21 21:22:33 13.09MB Practical Statistics Data Scientists
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Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analys
2018-03-18 16:08:03 6.62MB Hadoop
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