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. Youβll start by covering the mathematical prerequisites and the f
Deep Learning for Natural Language Processing. Creating Neural Networks with Python
β Scribed by Palash Goyal, Sumit Pandey, Karan Jain
- Publisher
- Apress
- Year
- 2018
- Tongue
- English
- Leaves
- 284
- Category
- Library
No coin nor oath required. For personal study only.
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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. Youβll start by covering the mathematical prerequisites and the
<div><p>Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such asΒ recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. </p><p>Youβll start by covering the mathematical prerequ
<p><b>Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues.</b></p> Key Features <li>Gain insights into the basic building blocks of natural language processing </li> <li>Learn how to select the best deep neural network to solve your
1 online resource (372 pages)
Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code