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                     <h1 class="hero-1-title mb-4 text-light">Practical Natural 
                        <span class="text-light ">Language Processing</span>
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                     <p class=" text-light " >Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, Harshit Surana</p>
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                     <p class="text-light mb-2 ">Endorsed by <span class="font-weight-medium" >Zachary Lipton, Sebastian Ruder & Marc Najork </span></p>
                     <p class="text-light mb-4 pb-2 ">Foreword by <span class="font-weight-medium" > Julian McAuley</span></p>
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                     <h1 class="hero-1-title mb-4 text-dark"> Practical NLP Is All You Need
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                        <strong>This book is your guide to build, iterate and scale NLP systems and to tailor them for various industry verticals</strong>
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                        This book is your guide to build, iterate and scale NLP systems in a business setting and to tailor them for various industry verticals.
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                     <h5 class="font-weight-bold text-dark">Increase your depth
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                        Consider the task of building a chatbot or text classification system at your organization. In the beginning there may be little or no data to work with. At this point a basic solution using rule based systems or traditional machine learning will be apt. As you accumulate more data, more sophisticated ML techniques (which are often data intensive) can be used including deep learning. At each step of this journey there are dozens of alternative approaches one can take. This book will help you navigate this maze of options.
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                        You will also learn to adapt your solutions for different industry verticals like healthcare, social media and retail. Moreover, you will learn about specific caveats you will encounter in each. You will learn how to analyze health records, detect fake news, extract attributes from e-commerce products and much more.
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                     <img src="images/quotes/zach.jpg">
                     <h4 class="text-light"><a href="http://zacklipton.com/">Zachary Lipton</a></h4>
                     <p class="text-light mb-0"> Scientist at Amazon AI</p>
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                        Author of Dive into Deep Learning
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                        Practical NLP focuses squarely on an overlooked demographic: the practitioners and business leaders in industry!           
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                     <h4 class="text-light"><a href="https://ruder.io/">Sebastian Ruder</a></h4>
                     <p class="text-light mb-0"> Scientist, Google DeepMind </p>
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                        Author of newsletter NLP News
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                        This book does a great job bridging the gap between natural language processing research and practical applications. 
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                     <h4 class="text-light"><a href="http://marc.najork.org">Marc Najork</a></h4>
                     <p class="text-light mb-0"> Director, Google AI</p>
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                        ACM & IEEE Fellow
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                        This book offers the best of both worlds: textbooks and 'cookbooks'. If you would like to go from zero to one in NLP, this book is for you! 
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                     <h4 class="text-light"><a href="https://www.microsoft.com/en-us/research/people/monojitc/">Monojit Choudhury</a></h4>
                     <p class="text-light mb-0"> Principal Researcher, Microsoft </p>
                     <p class=" text-light mb-0"> 
                        Faculty at IIT Kharagpur
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                        This book is a must for all aspiring NLP engineers, entrepreneurs who want to build companies around language technologies.
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                     <h4 class="text-light"><a href="https://www.linkedin.com/in/vinayakh/">Vinayak Hegde</a></h4>
                     <p class="text-light mb-0"> CTO-in-Residence</p>
                     <p class=" text-light mb-0"> 
                        Microsoft For Startups
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                        There is much hard-fought practical advice from the trenches. A must-read for engineers building NLP applications.
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                     <h4 class="text-light"><a href="https://mengtingwan.github.io/">Mengting Wan</a></h4>
                     <p class="text-light mb-0"> Data Scientist (ML & NLP) at Airbnb
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                        Microsoft Research Fellow
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                        I feel this is not only an essential book for NLP practitioners, it is also a valuable reference for the research community. 
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                     <h4 class="text-light"><a href="https://www.linkedin.com/in/siddharth-sharma-31140210/">Siddharth Sharma</a></h4>
                     <p class="text-light mb-0"> ML Engineer
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                        Facebook
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                        The authors achieved a rare feat by simplifying the esoteric art of design and architecture of production quality ML systems.
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                     <h4 class="text-light"><a href="https://www.linkedin.com/in/e10is/?originalSubdomain=ca">Ed Harris</a></h4>
                     <p class="text-light mb-0"> CEO and co-founder at 
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                        SharpestMinds (YC W18)
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                        This book gives a consolidated look at modern practice, starting from an MVP and building up to examples for sophisticated use cases.
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                     <h4 class="text-light"><a href="https://cseweb.ucsd.edu/~jmcauley/">Julian McAuley</a></h4>
                     <p class="text-light mb-0"> Professor at UC San Diego
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                        I am excited by the end-to-end approach taken in this book, which make it useful for a range of scenarios and help readers to work with the labyrinth of possible options while building NLP applications. I was thrilled to hear about efforts by Bodhisattwa, Sowmya, Anuj and Harshit to write a book on NLP. They have a wide experience in scaling NLP including at early-stage startups, the MIT Media Lab, Microsoft Research, and Google AI. This book is ideal both as a first resource to discover the field of natural language processing and a guide for seasoned practitioners looking to discover the latest developments in this exciting area. 
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                     <li class="lead">a software engineer or a data scientist who needs to build real-world NLP systems
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                     <li class="lead">a product manager who needs to understand NLP and how it can be applied to their domain
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                  <h4 class="text-light">Sowmya Vajjala</h4>
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                  <p class="text-light mb-3 f-15">Sowmya Vajjala has a PhD in Computational Linguistics from University of Tubingen, Germany. She currently works as a research officer at National Research Council, Canada’s largest federal research and development organization. Her past work experience spans both academia as a faculty at Iowa State University, USA and industry at Microsoft Research and The Globe and Mail.</p>
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                  <h4 class="text-light">Bodhisattwa Majumder</h4>
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                  <p class="text-light mb-3 f-15">Bodhisattwa Majumder is a doctoral candidate in NLP and ML at UC San Diego. Earlier he studied at IIT Kharagpur where he graduated summa cum laude. Previously, he built large-scale NLP systems at Google AI Research and Microsoft Research which went into products serving millions of users. Currently, he is also leading his university team in the Amazon Alexa Prize for 2019-2020.</p>
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                  <h4 class="text-light">Anuj Gupta</h4>
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                  <p class="text-light mb-3 f-15">Anuj Gupta has built NLP and ML systems at Fortune 100 companies as well as startups as a senior leader. He has incubated and led multiple ML teams in his career. He studied computer science at IIT Delhi and IIIT Hyderabad. He is currently Head of Machine Learning and Data Science at Vahan Inc. Above all, he is a father and husband.</p>
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                  <h4 class="text-light">Harshit Surana</h4>
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                  <p class="text-light mb-3 f-15">Harshit Surana is a co-founder at DeepFlux Inc. He has built and scaled ML systems and engineering pipelines at several Silicon Valley startups as a founder and an advisor. He studied computer science at Carnegie Mellon University where he worked with the MIT Media Lab on common sense AI. His research in NLP has received over 200 citations.</p>
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                           Through the course of the book, we will guide you through the process of building real-world NLP solutions embedded in larger product setups via a compendium of over 450 references. With this book, you’ll: 
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                           <li class="lead">Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP
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                           <li class="lead">Implement and evaluate different NLP applications using machine learning and deep learning methods
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                           <li class="lead">Fine-tune your NLP solution based on your business problem and industry vertical
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                           <li class="lead">Produce software solutions following best practices around release, deployment, and DevOps for NLP systems
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