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{ "item_title" : "Machine Learning with Tensorflow", "item_author" : [" Nishant Shukla "], "item_description" : "Summary Machine 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 Technology TensorFlow, 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 Book Machine 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 Reader Written for developers experienced with Python and algebraic concepts like vectors and matrices. About the Author Author 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 modelsPART 3 - THE NEURAL NETWORK PARADIGMA peek into autoencodersReinforcement learningConvolutional neural networksRecurrent neural networksSequence-to-sequence models for chatbotsUtility landscape", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/1/61/729/387/1617293873_b.jpg", "price_data" : { "retail_price" : "44.99", "online_price" : "44.99", "our_price" : "44.99", "club_price" : "44.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning with Tensorflow|Nishant Shukla

Machine Learning with Tensorflow

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Overview

Summary Machine 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 Technology TensorFlow, 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 Book Machine 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 Inside

  • Matching your tasks to the right machine-learning and deep-learning approaches
  • Visualizing algorithms with TensorBoard
  • Understanding and using neural networks

About the Reader Written for developers experienced with Python and algebraic concepts like vectors and matrices. About the Author Author 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 Contents
  1. PART 1 - YOUR MACHINE-LEARNING RIG
  2. A machine-learning odyssey
  3. TensorFlow essentialsPART 2 - CORE LEARNING ALGORITHMS
  4. Linear regression and beyond
  5. A gentle introduction to classification
  6. Automatically clustering data
  7. Hidden Markov modelsPART 3 - THE NEURAL NETWORK PARADIGM
  8. A peek into autoencoders
  9. Reinforcement learning
  10. Convolutional neural networks
  11. Recurrent neural networks
  12. Sequence-to-sequence models for chatbots
  13. Utility landscape

This item is Non-Returnable

Details

  • ISBN-13: 9781617293870
  • ISBN-10: 1617293873
  • Publisher: Manning Publications
  • Publish Date: February 2018
  • Dimensions: 9.2 x 7.4 x 0.5 inches
  • Shipping Weight: 1 pounds
  • Page Count: 272

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