{"product_id":"machine-learning-with-tensorflow-2-e-paperback","title":"Machine Learning with TensorFlow, 2\/E (Paperback)","description":"\u003cp\u003e\u003cspan style=\"color:#000000;\"\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:\u003eUpdated with new code, new projects, and new chapters, \u003c\/span\u003e\u003ci style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eMachine Learning with TensorFlow, Second Edition\u003c\/i\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e gives readers a solid foundation in machine-learning concepts and the TensorFlow library. Written by NASA JPL Deputy CTO and Principal Data Scientist Chris Mattmann, all examples are accompanied by downloadable Jupyter Notebooks for a hands-on experience coding TensorFlow with Python. New and revised content expands coverage of core machine learning algorithms, and advancements in neural networks such as VGG-Face facial identification classifiers and deep speech classifiers.\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:\u003eSupercharge your data analysis with machine learning! ML algorithms automatically improve as they process data, so results get better over time. You don’t have to be a mathematician to use ML: Tools like Google’s TensorFlow library help with complex calculations so you can focus on getting the answers you need.\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:\u003eMachine Learning with TensorFlow, Second Edition\u003c\/i\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e is a fully revised guide to building machine learning models using Python and TensorFlow. You’ll apply core ML concepts to real-world challenges, such as sentiment analysis, text classification, and image recognition. Hands-on examples illustrate neural network techniques for deep speech processing, facial identification, and auto-encoding with CIFAR-10.\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    Machine Learning with TensorFlow\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    Choosing the best ML approaches\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    Visualizing algorithms with TensorBoard\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    Sharing results with collaborators\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    Running models in Docker\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:\u003eRequires intermediate Python skills and knowledge of general algebraic concepts like vectors and matrices. Examples use the super-stable 1.15.x branch of TensorFlow and TensorFlow 2.x.\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:\u003eChris Mattmann\u003c\/b\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e is the Division Manager of the Artificial Intelligence, Analytics, and Innovation Organization at NASA Jet Propulsion Lab. The first edition of this book was written by \u003c\/span\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eNishant Shukla\u003c\/b\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e with \u003c\/span\u003e\u003cb style=\"font-family: \" amazon ember arial sans-serif font-size:\u003eKenneth Fricklas\u003c\/b\u003e\u003cspan style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e.\u003c\/span\u003e\u003c\/span\u003e\u003cbr style=\"font-family: \" amazon ember arial sans-serif font-size:\u003e \u003c\/p\u003e\u003cp\u003e\u003cb\u003eEbook License\u003c\/b\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\u003cbr\u003e\u003c\/p\u003e","brand":"Manning Publications","offers":[{"title":"Paperback","offer_id":50506209755206,"sku":"9781617297717","price":4432.0,"currency_code":"INR","in_stock":true},{"title":"E-Book","offer_id":50506209787974,"sku":"9781617297717-2","price":4333.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/411LBkHja_L.jpg?v=1790323212","url":"https:\/\/cb-india.com\/products\/machine-learning-with-tensorflow-2-e-paperback","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}