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Deep Learning for Natural Language Processing

You're reading from   Deep Learning for Natural Language Processing Solve your natural language processing problems with smart deep neural networks

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Product type Paperback
Published in Jun 2019
Publisher
ISBN-13 9781838550295
Length 372 pages
Edition 1st Edition
Languages
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Authors (4):
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Karthiek Reddy Bokka Karthiek Reddy Bokka
Author Profile Icon Karthiek Reddy Bokka
Karthiek Reddy Bokka
Monicah Wambugu Monicah Wambugu
Author Profile Icon Monicah Wambugu
Monicah Wambugu
Tanuj Jain Tanuj Jain
Author Profile Icon Tanuj Jain
Tanuj Jain
Shubhangi Hora Shubhangi Hora
Author Profile Icon Shubhangi Hora
Shubhangi Hora
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Table of Contents (11) Chapters Close

About the Book 1. Introduction to Natural Language Processing FREE CHAPTER 2. Applications of Natural Language Processing 3. Introduction to Neural Networks 4. Foundations of Convolutional Neural Network 5. Recurrent Neural Networks 6. Gated Recurrent Units (GRUs) 7. Long Short-Term Memory (LSTM) 8. State-of-the-Art Natural Language Processing 9. A Practical NLP Project Workflow in an Organization 1. Appendix

About the Authors

Karthiek Reddy Bokka is a speech and audio machine learning engineer graduate from the University of Southern California and is currently working for Bi-amp Systems in Portland. His interests include deep learning, digital signal and audio processing, natural language processing, and computer vision. He has experience in designing, building, and deploying applications with artificial intelligence to solve real-world problems with varied forms of practical data, including image, speech, music, unstructured raw data, and such.

Shubhangi Hora is a Python developer, artificial intelligence enthusiast, and a writer. With a background in computer science and psychology, she is particularly interested in mental health-related AI. She is based in Pune, India, and is passionate about furthering natural language processing through machine learning and deep learning. Apart from this, she enjoys the performing arts and is a trained musician.

Tanuj Jain is a data scientist working at a Germany-based company. He has been developing deep learning models and putting them in production for commercial use at his current job. Natural language processing is a special interest area for him, whereby he has applied his know-how to classification and sentiment rating tasks. He has a Master's degree in electrical engineering with a focus on statistical pattern recognition.

Monicah Wambugu is the lead data scientist at a financial technology company that offers micro-loans by leveraging on data, machine learning, and analytics to perform alternative credit scoring. She is a graduate student at the School of Information at UC Berkeley Masters in Information Management and Systems. Monicah is particularly interested in how data science and machine learning can be used to design products and applications that respond to the behavioral and socio-economic needs of target audiences.

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