Natural Language Processing with TensorFlow

Thushan Ganegedara

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商品描述

Key Features

  • Focus on natural language processing with TensorFlow, thereby avoiding the traditional focus on computer vision
  • Treats NLP as a field in its own right, and learn to process and evaluate large unstructured data sets consisting of text
  • Learn to apply the TensorFlow toolbox to the most interesting field in artificial intelligence

Book Description

TensorFlow is the most important deep learning framework currently in existence. Deep Learning algorithms are the most important frontier in artificial intelligence, with natural language processing (NLP) providing much of the engineering required to understand and process the vast majority of data available to deep learning applications today. Natural Language Processing with TensorFlow teaches aspiring deep learning developers to cope with unstructured data, that is, text and audio, which make up a large part of currently available data streams.

Thushan Ganegedara starts out by explaining the inner workings of TensorFlow itself, and the proceeds with a family of algorithms allowing sequences of words to be turned into vectors, making them accessible to deep learning algorithms in the process. He then shifts gears somewhat by showing how classical deep learning algorithms like convolutional neural networks (CNN) and recurrent neural (RNN) networks can be applied to NLP. Long short-term memory are a variety of RNNs, used in the next chapter for text generation.

Thushan concludes the book with an overview and implementation of neural machine translation, a method relying on deep learning algorithms to achieve impressive results in machine translation.

What you will learn

  • How to master NLP based on existing TensorFlow algorithms
  • Build NLP applications
  • Write automatic translation programs using neural machine translation algorithms
  • Use classical deep learning algorithms to classify sentences
  • Apply Long Short-Term Memory to text generation

商品描述(中文翻譯)

《自然語言處理與TensorFlow》

主要特點


  • 專注於使用TensorFlow進行自然語言處理,避免傳統對於計算機視覺的關注

  • 將NLP視為一個獨立的領域,學習處理和評估由文本組成的大型非結構化數據集

  • 學習將TensorFlow工具應用於人工智能中最有趣的領域

書籍描述

TensorFlow是目前最重要的深度學習框架。深度學習算法是人工智能中最重要的前沿領域,而自然語言處理(NLP)則提供了理解和處理當今深度學習應用中絕大部分可用數據所需的大部分工程。《自然語言處理與TensorFlow》教導有志於深度學習開發的人們如何處理非結構化數據,即文本和音頻,這是當前可用數據流的一大部分。

Thushan Ganegedara首先解釋了TensorFlow本身的內部運作方式,然後介紹了一系列算法,這些算法可以將詞序列轉換為向量,從而使它們可以被深度學習算法訪問。然後,他轉換了一些方向,展示了如何將傳統的深度學習算法,如卷積神經網絡(CNN)和循環神經網絡(RNN),應用於NLP。接下來的一章中,使用了一種RNN的變體——長短期記憶,用於文本生成。

Thushan最後概述並實現了神經機器翻譯,這是一種依賴於深度學習算法以實現在機器翻譯中取得令人印象深刻結果的方法。

你將學到什麼


  • 如何基於現有的TensorFlow算法掌握NLP

  • 構建NLP應用程式

  • 使用神經機器翻譯算法編寫自動翻譯程式

  • 使用傳統的深度學習算法對句子進行分類

  • 將長短期記憶應用於文本生成