Jalaj Thanaki - Python Natural Language Processing
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- Book:Python Natural Language Processing
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- Year:2018
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Jalaj Thanaki
BIRMINGHAM - MUMBAI
Copyright 2017 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, and its dealers and distributors will be held liable for any damages caused or alleged to be 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.
First published: July 2017
Production reference: 1280717
ISBN 978-1-78712-142-3
www.packtpub.com
Author Jalaj Thanaki | Copy Editor Safis Editing |
Reviewers Devesh Raj Gayetri Thakur Prabhanjan Tattar Chirag Mahapatra | Project Coordinator Manthan Patel |
Commissioning Editor Veena Pagare | Proofreader Safis Editing |
Acquisition Editor Aman Singh | Indexer Tejal Daruwale Soni |
ContentDevelopmentEditor Jagruti Babaria | Production Coordinator Deepika Naik |
Technical Editor Sayli Nikalje |
Data science is rapidly changing the world and the way we do business --be it retail, banking and financial services, publishing, pharmaceutical, manufacturing, and so on. Data of all forms is growing exponentially--quantitative, qualitative, structured, unstructured, speech, video, and so on. It is imperative to make use of this data to leverage all functions--avoid risk and fraud, enhance customer experience, increase revenues, and streamline operations.
Organizations are moving fast to embrace data science and investing a lot into high-end data science teams. Having spent more than 12 years in the BFSI domain, I get overwhelmed with the transition that the BFSI industry has seen in embracing analytics as a business and no longer a support function. This holds especially true for the fin-tech and digital lending world of which Jalaj and myself are a part of.
I have known Jalaj since her college days and am impressed with her exuberance and self-motivation. Her research skills, perseverance, commitment, discipline, and quickness to grasp even the most difficult concepts have made her achieve success in a short span of 4 years on her corporate journey.
Jalaj is a gifted intellectual with a strong mathematical and statistical understanding and demonstrates a continuous passion for learning the new and complex analytical and statistical techniques that are emerging in the industry. She brings experience to the data science domain and I have seen her deliver impressive projects around NLP, machine learning, basic linguistic analysis, neural networks, and deep learning. The blistering pace of the work schedule that she sets for herself, coupled with the passion she puts into her work, leads to definite and measurable results for her organization.
One of her most special qualities is her readiness to solve the most basic to the most complex problem in the interest of the business. She is an excellent team player and ensures that the organization gains the maximum benefit of her exceptional talent.
In this book, Jalaj takes us on an exciting and insightful journey through the natural language processing domain. She starts with the basic concepts and moves on to the most advanced concepts, such as how machine learning and deep learning are used in NLP.
I wish Jalaj all the best in all her future endeavors.
Sarita Arora
Chief Analytics Officer, SMECorner
Mumbai, India
Jalaj Thanaki is a data scientist by profession and data science researcher by practice. She likes to deal with data science related problems. She wants to make the world a better place using data science and artificial intelligence related technologies. Her research interest lies in natural language processing, machine learning, deep learning, and big data analytics. Besides being a data scientist, Jalaj is also a social activist, traveler, and nature-lover.
I would like to dedicate this book to my husband, Shetul Thanaki, for his constant support, encouragement, and creative suggestions.
I give deep thanks and gratitude to my parents, my in-laws, my family, and my friends, who have helped me at every stage of my life. I would also like to thank all the mentors that I've had over the years. I really appreciate the efforts by technical reviewers for reviewing this book. I would also like to thank my current organization, SMECorner, for its support. I am a big fan of open source communities and education communities, so I really want to thank communities such as Kaggel, Udacity, and Coursera who have helped me, in a direct or indirect manner, to understand the various concepts of data science. Without learning from these communities, there is not a chance I could be doing what I do today.
I would like to thank Packt Publishing and Aman Singh, who approached me to write this book. I really appreciate the effort put in by the entire Packt editorial team to make this book as good as possible. Special thanks to Aman Singh, Jagruti Babaria, Menka Bohra, Manthan Patel, Nidhi Joshi, Sayli Nikalje, Manisha Sinha, Safis, and Tania Dutta.
I would like to recognize the efforts of technical editing team, strategy and management team, marketing team, sales team, graphics designer team, pre-production team, post production team, layout coordinators team, and indexer team for making my authoring journey so smooth.
I feel really compelled to pass my knowledge on to those willing to learn.
Thank you God for being kind to me!
Cheers and Happy Reading!
Devesh Raj is a data scientist with 10 years of experience in developing algorithms and solving problems in various domains--healthcare, manufacturing, automotive, production, and so on, applying machine learning (supervised and unsupervised machine learning techniques) and deep learning on structured and unstructured data (computer vision and NLP).
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