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Thomas Dop - Hands-On Natural Language Processing with PyTorch 1.x: Build smart, AI-driven linguistic applications using deep learning and NLP techniques

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Thomas Dop Hands-On Natural Language Processing with PyTorch 1.x: Build smart, AI-driven linguistic applications using deep learning and NLP techniques
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Become a proficient NLP data scientist by developing deep learning models for NLP and extract valuable insights from structured and unstructured data Key Features Get to grips with word embeddings, semantics, labeling, and high-level word representations using practical examples Learn modern approaches to NLP and explore state-of-the-art NLP models using PyTorch Improve your NLP applications with innovative neural networks such as RNNs, LSTMs, and CNNs Book Description In the internet age, where an increasing volume of text data is generated daily from social media and other platforms, being able to make sense of that data is a crucial skill. With this book, youll learn how to extract valuable insights from text by building deep learning models for natural language processing (NLP) tasks. Starting by understanding how to install PyTorch and using CUDA to accelerate the processing speed, youll explore how the NLP architecture works with the help of practical examples. This PyTorch NLP book will guide you through core concepts such as word embeddings, CBOW, and tokenization in PyTorch. Youll then learn techniques for processing textual data and see how deep learning can be used for NLP tasks. The book demonstrates how to implement deep learning and neural network architectures to build models that will allow you to classify and translate text and perform sentiment analysis. Finally, youll learn how to build advanced NLP models, such as conversational chatbots. By the end of this book, youll not only have understood the different NLP problems that can be solved using deep learning with PyTorch, but also be able to build models to solve them. What you will learn Use NLP techniques for understanding, processing, and generating text Understand PyTorch, its applications and how it can be used to build deep linguistic models Explore the wide variety of deep learning architectures for NLP Develop the skills you need to process and represent both structured and unstructured NLP data Become well-versed with state-of-the-art technologies and exciting new developments in the NLP domain Create chatbots using attention-based neural networks Who this book is for This PyTorch book is for NLP developers, machine learning and deep learning developers, and anyone interested in building intelligent language applications using both traditional NLP approaches and deep learning architectures. If youre looking to adopt modern NLP techniques and models for your development projects, this book is for you. Working knowledge of Python programming, along with basic working knowledge of NLP tasks, is required.

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Thomas Dop - Hands-On Natural Language Processing with PyTorch 1.x: Build smart, AI-driven linguistic applications using deep learning and NLP techniques
Hands-On Natural Language Processing with PyTorch 1.x: Build smart, AI-driven linguistic applications using deep learning and NLP techniques
Thomas Dop
Hands-On Natural Language Processing with PyTorch 1.x: Build smart, AI-driven linguistic applications using deep learning and NLP techniques

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Hands-On Natural Language Processing with PyTorch 1x Build smart AI-driven - photo 1
Hands-On Natural Language Processing with PyTorch 1.x

Build smart, AI-driven linguistic applications using deep learning and NLP techniques

Thomas Dop

BIRMINGHAMMUMBAI Hands-On Natural Language Processing with PyTorch 1x - photo 2

BIRMINGHAMMUMBAI

Hands-On Natural Language Processing with PyTorch 1.x

Copyright 2020 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

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First published: July 2020

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Published by Packt Publishing Ltd.

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ISBN 978-1-78980-274-0

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For Mhairi and Dr. F.R. Allen

Thomas Dop

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Contributors
About the author

Thomas Dop is a data scientist at MagicLab, a company that creates leading dating apps, including Bumble and Badoo. He works on a variety of areas within data science, including NLP, deep learning, computer vision, and predictive modeling. He holds an MSc in data science from the University of Amsterdam.

About the reviewers

Nilan Saha is pursuing a Masters degree in Data Science with a specialization in Computational Linguistics from the University of British Columbia, Canada. He has worked as an NLP contractor for multiple startups in the past, and has also got brief experience in research, which has resulted in a few publications. He is also a Kaggle Kernels and Discussion Expert.

Chintan Gajjar is a senior consultant in KNOWARTH Technologies. He has also contributed to books such as Hadoop Backup and Recovery Solutions, MySQL 8 for Big Data, MySQL 8 Administrators Guide, and Hands-on Natural Language Processing with Python. He has a Masters degree in computer applications from Ganpat University, India.

I would like to thank the author, co-reviewer, and the wonderful team at Packt Publishing for all efforts and my office colleagues, Darshan Kansara and Kathan Thakkar, for supporting me throughout the reviewing of this book. They both are technology enthusiasts and have a great understanding of AI/ML, CI-CD, and are great mentors.

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