{"product_id":"deep-learning-with-structured-data","title":"Deep Learning with Structured Data","description":"\u003cp\u003e\u003ci style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eDeep Learning with Structured Data\u003c\/i\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e teaches you powerful data analysis techniques for tabular data and relational databases.\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eSummary\u003c\/b\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eDeep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. \u003c\/span\u003e\u003ci style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eDeep Learning with Structured Data\u003c\/i\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems.\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003ePurchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eAbout the technology\u003c\/b\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eHere’s a dirty secret: Half of the time in most data science projects is spent cleaning and preparing data. But there’s a better way: Deep learning techniques optimized for tabular data and relational databases deliver insights and analysis without requiring intense feature engineering. Learn the skills to unlock deep learning performance with much less data filtering, validating, and scrubbing.\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eAbout the book\u003c\/b\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003ci style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eDeep Learning with Structured Data\u003c\/i\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e teaches you powerful data analysis techniques for tabular data and relational databases. Get started using a dataset based on the Toronto transit system. As you work through the book, you’ll learn how easy it is to set up tabular data for deep learning, while solving crucial production concerns like deployment and performance monitoring.\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eWhat's inside\u003c\/b\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e    When and where to use deep learning\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e    The architecture of a Keras deep learning model\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e    Training, deploying, and maintaining models\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e    Measuring performance\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eAbout the reader\u003c\/b\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eFor readers with intermediate Python and machine learning skills.\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eAbout the author\u003c\/b\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eMark Ryan\u003c\/b\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e is a Data Science Manager at Intact Insurance. He holds a Master's degree in Computer Science from the University of Toronto.\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eTable of Contents\u003c\/b\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e1 Why deep learning with structured data?\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e2 Introduction to the example problem and Pandas dataframes\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e3 Preparing the data, part 1: Exploring and cleansing the data\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e4 Preparing the data, part 2: Transforming the data\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e5 Preparing and building the model\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e6 Training the model and running experiments\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e7 More experiments with the trained model\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e8 Deploying the model\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e9 Recommended next steps\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eEbook License\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eEnd-User Warranty And License Agreement\u003c\/p\u003e\u003cp\u003e1. Grant Of License\u003c\/p\u003e\u003cp\u003eManning Has Authorized The Download By You Of An Unrestricted Number Of Copies Of The Electronic Book (Ebook) In Any Of The Available Formats. Manning Grants You A Nonexclusive, Nontransferable License To Use The Ebook According To The Terms And Conditions Herein. This License Agreement Permits You To Install The Ebook On Any And All Your Devices For Your Personal Use Only.\u003c\/p\u003e\u003cp\u003e2. Restrictions\u003c\/p\u003e\u003cp\u003eYou Shall Not: (1) Share, Resell, Rent, Assign, Timeshare, Distribute, Or Transfer All Or Part Of The Ebook Or Any Rights Granted Hereunder To Any Other Person; (2) Duplicate The Ebook, Except For A Single Backup Or Archival Copy; (3) Remove Any Proprietary Notices, Labels, Or Marks From The Ebook; (4) Transfer Or Sublicense Title To The Ebook To Any Other Party.\u003c\/p\u003e\u003cp\u003e3. Intellectual Property Protection\u003c\/p\u003e\u003cp\u003eThe Ebook Is Owned By Manning And Is Protected By United States And International Copyright And Other Intellectual Property Laws. Manning Reserves All Rights In The Ebook Not Expressly Granted Herein. This License And Your Right To Use The Ebook Terminate Automatically If You Violate Any Part Of This Agreement. In The Event Of Termination, You Must Remove The Original And Any Copies Of The Ebook From All Your Devices.\u003c\/p\u003e\u003cp\u003e4. Source Code Supplementary Material\u003c\/p\u003e\u003cp\u003eAny Source Code Files Provided As A Supplement To The Book Are Freely Available To The Public For Download. Reuse Of The Code Is Permitted, In Whole Or In Part, Including The Creation Of Derivative Works, Provided That You Acknowledge That You Are Using It And Identify The Source: Title, Publisher And Year.\u003c\/p\u003e\u003cp\u003e5. Limited Warranty\u003c\/p\u003e\u003cp\u003eManning Warrants That The Ebook Files, A Copy Of Which You Are Authorized To Download, Are Free From Defects In The Operational Sense That They Can Be Read By A Pdf Reader Or Epub Reader, Or Other. Except For This Express Limited Warranty, Manning Makes And You Receive No Warranties, Express, Implied, Statutory Or In Any Communication With You, And Manning Specifically Disclaims Any Other Warranty Including The Implied Warranty Of Merchantability Or Fitness Or A Particular Purpose. Manning Does Not Warrant That The Operation Of The Ebook Will Be Uninterrupted Or Error Free. If The Ebook Was Purchased In The United States, The Above Exclusions May Not Apply To You As Some States Do Not Allow The Exclusion Of Implied Warranties. In Addition To The Above Warranty Rights, You May Also Have Other Rights That Vary From State To State.\u003c\/p\u003e\u003cp\u003e6. Limitation Of Liability\u003c\/p\u003e\u003cp\u003eIn No Event Will Manning Be Liable For Any Damages, Whether Arising For Tort Or Contract, Including Loss Of Data, Lost Profits, Or Other Special, Incidental, Consequential, Or Indirect Damages Arising Out Of The Use Or Inability To Use The Ebook.\u003c\/p\u003e\u003cp\u003e7. General\u003c\/p\u003e\u003cp\u003eThis Agreement Constitutes The Entire Agreement Between You And Manning And Supersedes Any Prior Agreement Concerning The Ebook. This Agreement Is Governed By The Laws Of The State Of New York.\u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e","brand":"Manning Publications","offers":[{"title":"Paperback","offer_id":50506208542790,"sku":"9781617296727","price":3841.0,"currency_code":"INR","in_stock":true},{"title":"E-Book","offer_id":50506208575558,"sku":"9781617296727-2","price":4333.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/9781617296727.jpg?v=1790323169","url":"https:\/\/cb-india.com\/products\/deep-learning-with-structured-data","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}