Machine Learning With Tensorflow(1st Edition)
Authors:
Nishant Shukla
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ISBN: 1617293873, 978-1617293870
Book publisher: Manning
Book Price $0 : SummaryMachine Learning With TensorFlow Gives Readers A Solid Foundation In Machine-learning Concepts Plus Hands-on Experience Coding TensorFlow With Python. Purchase Of The Print Book Includes A Free EBook In PDF, Kindle, And EPub Formats From Manning Publications.About The TechnologyTensorFlow, Google's Library For Large-scale Machine Learning, Simplifies Often-complex Computations By Representing Them As Graphs And Efficiently Mapping Parts Of The Graphs To Machines In A Cluster Or To The Processors Of A Single Machine.About The BookMachine Learning With TensorFlow Gives Readers A Solid Foundation In Machine-learning Concepts Plus Hands-on Experience Coding TensorFlow With Python. You'll Learn The Basics By Working With Classic Prediction, Classification, And Clustering Algorithms. Then, You'll Move On To The Money Chapters: Exploration Of Deep-learning Concepts Like Autoencoders, Recurrent Neural Networks, And Reinforcement Learning. Digest This Book And You Will Be Ready To Use TensorFlow For Machine-learning And Deep-learning Applications Of Your Own. What's InsideMatching Your Tasks To The Right Machine-learning And Deep-learning ApproachesVisualizing Algorithms With TensorBoardUnderstanding And Using Neural NetworksAbout The ReaderWritten For Developers Experienced With Python And Algebraic Concepts Like Vectors And Matrices.About The AuthorAuthor Nishant Shukla Is A Computer Vision Researcher Focused On Applying Machine-learning Techniques In Robotics. Senior Technical Editor, Kenneth Fricklas, Is A Seasoned Developer, Author, And Machine-learning Practitioner.Table Of ContentsPART 1 - YOUR MACHINE-LEARNING RIGA Machine-learning OdysseyTensorFlow EssentialsPART 2 - CORE LEARNING ALGORITHMSLinear Regression And BeyondA Gentle Introduction To ClassificationAutomatically Clustering DataHidden Markov Models PART 3 - THE NEURAL NETWORK PARADIGMA Peek Into AutoencodersReinforcement LearningConvolutional Neural NetworksRecurrent Neural NetworksSequence-to-sequence Models For ChatbotsUtility Landscape
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