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Deep learning for natural language processing :creating neural networks with Python /
作者 : Goyal, Palash. , Pandey, Sumit. , Jain, Karan.
出版社 : Apress :
出版年 : 2018
ISBN：9781484236840
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書名 ： Deep learning for natural language processing :creating neural networks with Python /
紀錄類型 ： 書目-語言資料,印刷品: 單行本
正題名[資料類型標示]/作者 ： Deep learning for natural language processing :by Palash Goyal, Sumit Pandey, Karan Jain.
其他題名 ： creating neural networks with Python /
作者 ： Goyal, Palash.
其他作者 ： Pandey, Sumit.
出版者 ： Berkeley, CA :Apress :2018.
面頁冊數 ： xvii, 277 pages ;24 cm.
內容註 ： Chapter 1: Introduction to NLP and Deep Learning -- Chapter 2: Word Vector representations -- Chapter 3: Unfolding Recurrent Neural Networks -- Chapter 4: Developing a Chatbot -- Chapter 5: Research Paper Implementation: Sentiment Classification.
標題 ： Natural language processing (Computer science).
ISBN ： 9781484236840 (pbk.) :
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090 $a臺南市立圖書館
100 1 $aGoyal, Palash.
245 10$aDeep learning for natural language processing :$bcreating neural networks with Python /$cby Palash Goyal, Sumit Pandey, Karan Jain.
260 $aBerkeley, CA :$bApress :$c2018.$bImprint: Apress,
300 $axvii, 277 pages ;$c24 cm.
505 0 $aChapter 1: Introduction to NLP and Deep Learning -- Chapter 2: Word Vector representations -- Chapter 3: Unfolding Recurrent Neural Networks -- Chapter 4: Developing a Chatbot -- Chapter 5: Research Paper Implementation: Sentiment Classification.
520 $aDiscover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You'll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with practical examples. The first three chapters of the book cover the basics of NLP, starting with word- vector representation before moving onto advanced algorithms. The final chapters focus entirely on implementation, and deal with sophisticated architectures such as RNN, LSTM, and Seq2seq, using Python tools: TensorFlow, and Keras. Deep Learning for Natural Language Processing follows a progressive approach and combines all the knowledge you have gained to build a question-answer chatbot system. This book is a good starting point for people who want to get started in deep learning for NLP. All the code presented in the book will be available in the form of IPython notebooks and scripts, which allow you to try out the examples and extend them in interesting ways. You will: Gain the fundamentals of deep learning and its mathematical prerequi
650 0$aNatural language processing (Computer science).
650 0$aNeural networks (Computer science).
650 0$aPython (Computer program language).
650 14$aComputer Science.
650 24$aComputing Methodologies.
650 24$aPython.
650 24$aOpen Source.
653 $a青少年
700 1 $aPandey, Sumit.
700 1 $aJain, Karan.