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  • 醉染图书TensorFlow自然语言处理()9787564182892
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    • 作者: (澳)苏尚·甘吉达拉(Thushan Ganegedara)著 | (澳)苏尚·甘吉达拉(Thushan Ganegedara)编 | (澳)苏尚·甘吉达拉(Thushan Ganegedara)译 | (澳)苏尚·甘吉达拉(Thushan Ganegedara)绘
    • 出版社: 东南大学出版社
    • 出版时间:2019-03-01
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    • 作者: (澳)苏尚·甘吉达拉(Thushan Ganegedara)著| (澳)苏尚·甘吉达拉(Thushan Ganegedara)编| (澳)苏尚·甘吉达拉(Thushan Ganegedara)译| (澳)苏尚·甘吉达拉(Thushan Ganegedara)绘
    • 出版社:东南大学出版社
    • 出版时间:2019-03-01
    • 版次:1
    • 印次:1
    • 字数:578千字
    • 页数:446
    • 开本:16开
    • ISBN:9787564182892
    • 国别/地区:中国
    • 版权提供:东南大学出版社
    • 作者:(澳)苏尚·甘吉达拉(Thushan Ganegedara)
    • 著:(澳)苏尚·甘吉达拉(Thushan Ganegedara)
    • 装帧:平装
    • 印次:1
    • 定价:106.00
    • ISBN:9787564182892
    • 出版社:东南大学出版社
    • 开本:16开
    • 印刷时间:暂无
    • 语种:暂无
    • 出版时间:2019-03-01
    • 页数:446
    • 外部编号:1201871665
    • 版次:1
    • 成品尺寸:暂无

    Preface
    Chapter 1: Introduction to Natural Language Processing
    What is Natural Language Processing?
    Tasks of Natural Language Processing
    The traditional approach to Natural Language Processing
    Understanding the traditional approach
    Example - generating football game summaries
    Drawbacks of the traditional approach
    The deep learning approach to Natural Language Processing
    History of deep learning
    The currensttef deep learning and NLP
    Understanding a simple deep model - a Fully-Connected Neural Network
    The roadmap - beyond this chapter
    Introduction to the technical tools
    Description of the tools
    Installing Python and scikit-learn
    Installing Jupyter Notebook
    Installing TensorFlow
    Summary
    Chapter 2: Understanding TensorFlow
    What is TensorFlow?
    Getting started with TensorFlow
    TensorFlow client in detail
    TensorFlow architecture - what happens when you execute the client?
    Cafe Le TensorFlow - understanding TensorFlow with an analogy
    Inputs, variables, outpus,ndraios
    Defining inputs in TensorFlow
    Feeding data with Python code
    Preloading and storing data as tensors
    Building an input pipeline
    Defining variables in TensorFlow
    Defining TensorFlow outputs
    Defining TensorFlow oraios
    Comparison oraios
    Mathematical oraios
    Scatter and gather oraios
    Neural network-related oraios
    Reusing variables with scoping
    Implementing our first neural network
    Preparing the data
    Defining the TensorFlow graph
    Running the neural network
    Summary
    Chapter 3: Word2vec - Learning Word Embeddings
    What is a word representation or meaning?
    Classical approaches to learning word representation
    WordNet - using an external lexical knowledge base for learning word representations
    Tour of WordNet
    Problems with WordNet
    One-hot encoded representation
    The TF-F method
    Co-occurrence matrix
    Word2vec - a neural network-based approach to learning word representation
    Exercise: is queen = king - he + she?
    Designing a loss function for learning word embeddings
    The skip-gram algorithm
    From raw text to structured data
    Learning the word embeddings with a neural network
    Formulating a practical loss function
    Efficiently approximating the loss function
    Implementing skip-gram with TensorFlow
    The Continuous Bag-of-Words algorithm
    Implementing CBOW in TensorFlow
    Summary
    Chapter 4: Advanced Word2vec
    The original skip-gram algorithm
    Implementing the original skip-gram algorithm
    ……
    Chapter 5: Sentence Classification with Convolutional Neural Networks
    Chapter 6: Recurrent Neural Networks
    Chapter 7: Lonq Short-Term Memory_ Networks
    Chapter 8: Applications of LSTM - Generating Text
    Chapter 9: Applications of LSTM - Image Caption Generation
    Chapter 10: Sequence-to-Sequence Learning - Neural Machine Translation
    Chapter 11: Current Trends and the Future of Natural Language Processing
    Appendix: Mathematical Foundations and Advanced TensorFlow
    Other Books You May Enjoy
    Index

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