rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: TensorFlow in action
  name:
    name part: Ganegedara, Thushan
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  origin info:
    place:
      place term: nyu
    date issued: 2022
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (1 volume.) : illustrations
  abstract: In TensorFlow in Action, you'll dig into the newest version of Google's amazing TensorFlow framework as you learn to create incredible deep learning applications. Author Thushan Ganegedara uses quirky stories, practical examples, and behind-the-scenes explanations to demystify concepts otherwise trapped in dense academic papers. As you dive into modern deep learning techniques like transformer and attention models, you'll benefit from the unique insights of a top StackOverflow contributor for deep learning and NLP.
  table of contents: Intro -- TensorFlow in Action -- Copyright -- dedication -- contents -- front matter -- preface -- acknowledgments -- about this book -- Who should read this book? -- How this book is organized: A roadmap -- About the code -- liveBook discussion forum -- about the author -- about the cover illustration -- Part 1 Foundations of TensorFlow 2 and deep learning -- 1 The amazing world of TensorFlow -- 1.1 What is TensorFlow? -- 1.1.1 An overview of popular components of TensorFlow -- 1.1.2 Building and deploying a machine learning model -- 1.2 GPU vs. CPU -- 1.3 When and when not to use TensorFlow
  table of contents: 1.3.1 When to use TensorFlow -- 1.3.2 When not to use TensorFlow -- 1.4 What will this book teach you? -- 1.4.1 TensorFlow fundamentals -- 1.4.2 Deep learning algorithms -- 1.4.3 Monitoring and optimization -- 1.5 Who is this book for? -- 1.6 Should we really care about Python and TensorFlow 2? -- Summary -- 2 TensorFlow 2 -- 2.1 First steps with TensorFlow 2 -- 2.1.1 How does TensorFlow operate under the hood? -- 2.2 TensorFlow building blocks -- 2.2.1 Understanding tf.Variable -- 2.2.2 Understanding tf.Tensor -- 2.2.3 Understanding tf.Operation
  table of contents: 2.3 Neural network-related computations in TensorFlow -- 2.3.1 Matrix multiplication -- 2.3.2 Convolution operation -- 2.3.3 Pooling operation -- Summary -- Answers to exercises -- 3 Keras and data retrieval in TensorFlow 2 -- 3.1 Keras model-building APIs -- 3.1.1 Introducing the data set -- 3.1.2 The Sequential API -- 3.1.3 The functional API -- 3.1.4 The sub-classing API -- 3.2 Retrieving data for TensorFlow/Keras models -- 3.2.1 tf.data API -- 3.2.2 Keras DataGenerators -- 3.2.3 tensorflow-datasets package -- Summary -- Answers to exercises -- 4 Dipping toes in deep learning
  table of contents: 4.1 Fully connected networks -- 4.1.1 Understanding the data -- 4.1.2 Autoencoder model -- 4.2 Convolutional neural networks -- 4.2.1 Understanding the data -- 4.2.2 Implementing the network -- 4.3 One step at a time: Recurrent neural networks (RNNs) -- 4.3.1 Understanding the data -- 4.3.2 Implementing the model -- 4.3.3 Predicting future CO2 values with the trained model -- Summary -- Answers to exercises -- 5 State-of-the-art in deep learning: Transformers -- 5.1 Representing text as numbers -- 5.2 Understanding the Transformer model -- 5.2.1 The encoder-decoder view of the Transformer
  table of contents: 5.2.2 Diving deeper -- 5.2.3 Self-attention layer -- 5.2.4 Understanding self-attention using scalars -- 5.2.5 Self-attention as a cooking competition -- 5.2.6 Masked self-attention layers -- 5.2.7 Multi-head attention -- 5.2.8 Fully connected layer -- 5.2.9 Putting everything together -- Summary -- Answers to exercises -- Part 2 Look ma, no hands! Deep networks in the real world -- 6 Teaching machines to see: Image classification with CNNs -- 6.1 Putting the data under the microscope: Exploratory data analysis -- 6.1.1 The folder/file structure -- 6.1.2 Understanding the classes in the data set
  note: Thushan Ganegedara.
  note: Includes index.
  note: Covers TensorFlow version 2.9.
  subject:
    topic: Machine learning
  subject:
    topic: Artificial intelligence
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Apprentissage automatique
  subject:
    topic: Intelligence artificielle
  subject:
    topic: artificial intelligence
  subject:
    topic: Artificial intelligence
  subject:
    topic: Machine learning
  classification: Q325.5
  classification: 006.3/1
  related item:
    title info:
      title: Tensorflow 2.0 in action
    name:
      name part: Ganegedara, Thushan.
    origin info:
      publisher: Shelter Island : Manning Publications, 2022
    identifier: (OCoLC)1289279869
  identifier: 9781617298349
  identifier: 1617298344
  identifier: 9781638356738
  identifier: 1638356734
  identifier: 9781617298349 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: ORMDA
    record creation date: 221018
    record change date: 20260129211955.7
    record identifier: in00004672499
    language of cataloging:
      language term: eng