MARC details
| 000 -LEADER |
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| fixed length control field |
01921nam a22002537a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20221122122728.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
221122b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781484246016 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.35 |
| Item number |
GOY |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Goyal, Palash |
| 245 ## - TITLE STATEMENT |
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| Title |
Deep learning for natural language processing: |
| Remainder of title |
creating neural networks with python |
| 250 ## - EDITION STATEMENT |
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| Edition statement |
2nd |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc. |
Apress |
| Place of publication, distribution, etc. |
New York |
| Date of publication, distribution, etc. |
2021 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xvii, 277 p. |
| 365 ## - TRADE PRICE |
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| Price type code |
INR |
| Price amount |
829.00 |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
About this book<br/>Discover 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.<br/><br/>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.<br/><br/>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. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Python (Computer program language) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Neural networks (Computer science) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Natural language processing (Computer science) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Machine learning |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Pandey, Sumit |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Jain, Karan |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |