• Machine Learning with TensorFlow

Machine Learning with TensorFlow

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Est. Date: Nov 29, 2025

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

  • Author(s): Nishant Shukla
  • Publisher: Manning
  • Language: en
  • Pages: 272
  • Binding: Paperback
  • Edition: First Edition
  • Published: 2018-02-12
  • Dimensions: Height: 9.25 Inches, Length: 7.38 Inches, Weight: 1.00089866948 Pounds, Width: 0.7 Inches
  • Estimated Delivery: Nov 29, 2025
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