Practical Natural Language Processing : A Comprehensive Guide to Building Real-World NLP Systems

Author: Sowmya Vajjala

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9789385889189
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    All Indian Reprints of O'Reilly are printed in Grayscale

    Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. 

    Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You'll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. 

    With this book, you'll: 

    • Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP 
    • Implement and evaluate different NLP applications using machine learning and deep learning methods 
    • Fine-tune your NLP solution based on your business problem and industry vertical 
    • Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages 
    • Produce software solutions following best practices around release, deployment, and DevOps for NLP systems 
    • Understand best practices, opportunities, and the roadmap for NLP from a business and product leader's perspective 
    • Show and hide more

    From the Publisher

    How Practical NLP was born

    The authors have been building and scaling NLP solutions for over a decade at leading universities and technology companies. While mentoring colleagues and other engineers, they noticed a gap between NLP practice in the industry and the NLP skill set of new engineers or those who are experienced but just starting with NLP in particular. Authors started understanding these gaps even better with NLP workshops they were conducting for industry professionals where they noticed that business and engineering leaders also suffer from these gaps.

    Most of the online courses and books tackle NLP problems using toy use cases and popular (often large, clean and well defined) datasets. While this teaches the readers general methods, authors have seen that it does not give enough foundation to tackle new problems and develop complete solutions in the real world. Commonly encountered problems while building real world applications such as data collection, working with noisy data and signals, incremental development of solutions, and issues involved in deploying the solutions as a part of a larger application are generally not dealt with by existing resources on the topic. They also saw best practices to develop NLP systems were missing in most scenarios and this book was needed to bridge this gap.

    What the book covers

    This book gives a comprehensive view on building real world NLP applications. it covers the complete lifecycle of a typical NLP project - right from data collection to deploying and monitoring the model. Some of these steps are applicable to any ML pipeline while some are very specific to NLP. The book also introduces task-specific case studies and domain-specific guides to build an NLP system from scratch. Specifically it covers a gamut tasks ranging from text classification to question answering, information extraction to dialog systems. Similarly, it provides recipes to apply these tasks in domains ranging from e-commerce to healthcare, social media to law. The book also covers case studies and best practices from the viewpoint of business, engineering and product leaders to help them run NLP projects smoothly.

    Owing to the depth and breadth of the topics and scenarios that are covered, the book does not go step by step explaining the code and all the concepts. Please refer to the detailed source code notebooks for details of the implementation. The code snippets given in the book cover the core logic and often skip introductory steps like setting up a library or importing a package as they are covered in the associated notebooks. To cover the wide range of concepts the book provides more than 450 extensive references to delve deeper into these topics. This book will be a day-to-day cookbook giving you a pragmatic view while building any NLP system as well as be a stepping stone to broaden the application of NLP into your domain.

    Please note that readers pursuing cutting-edge research in NLP may find some sections of the book rudimentary as it does not cover in-depth theoretical and technical details related to NLP concepts. Moreover, it is expected that the readers will follow the respective documentations for various frameworks used in the code examples.

      Natural Language Processing Natural Language Processing, python Natural Language Processing, pytorch Natural Language Processing, spark
      Practical Natural Language Processing Natural Language Processing with Python Natural Language Processing with PyTorch Natural Language Processing with Spark NLP
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    Editorial Reviews

    Review

    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. 

    Julian McAuley, Professor, UC San Diego

    Practical NLP focuses squarely on an overlooked demographic: the practitioners and business leaders in industry!  

    Zachary Lipton, Scientist at Amazon AI, Author of Dive into Deep Learning, Professor, Carnegie Mellon University

    This book does a great job bridging the gap between natural language processing research and practical applications.

    Sebastian Ruder Scientist, Google DeepMind, Author of newsletter NLP News

    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!

    Marc Najork, Director, Google AI, ACM & IEEE Fellow

    This book is a must for all aspiring NLP engineers, entrepreneurs who want to build companies around language technologies.

    Monojit Choudhury, Principal Researcher, Microsoft, Faculty at IIT Kharagpur

    There is much hard-fought practical advice from the trenches. A must-read for engineers building NLP applications.

    Vinayak Hegde, CTO-in-Residence, Microsoft For Startups

    I feel this is not only an essential book for NLP practitioners, it is also a valuable reference for the research community.

    Mengting Wan, Data Scientist at Airbnb, Microsoft Research Fellow

    The authors achieved a rare feat by simplifying the esoteric art of design and architecture of production quality ML systems.

    Siddharth Sharma, ML Engineer, Facebook

    This book gives a consolidated look at modern practice, starting from an MVP and building up to examples for sophisticated use cases.

    Ed Harris, CEO and co-founder at SharpestMinds (YC W18)

    From the Author

    We wrote the book for:
     
    • A software engineer or a data scientist who needs to build real-world NLP systems
    • A machine learning engineer who has to iterate and scale NLP systems
    • A product manager who needs to understand NLP and how it can be applied to their domain
    • A business leader who wants to start a new venture based on NLP or incorporate the cutting edge of NLP in existing products

     

    Please note that readers pursuing cutting-edge research in NLP may find some sections of the book rudimentary as we do not cover in-depth theoretical and technical details related to NLP concepts. Moreover, we expect the readers to follow the respective documentations for various frameworks we use in our code examples.
    Books
    Author
    Sowmya Vajjala
    Author 2
    Bodhisattwa Majumder
    Author 3
    Anuj Gupta
    Author 4
    Harshit Surana
    Binding
    Paperback
    Condition Type
    New
    Country Origin
    India
    Edition
    First
    Gift Wrap
    N
    Leadtime to ship in days (default)
    ships in 1-2 days
    Pages
    456
    Publication Date
    05/08/2020
    Publisher
    Shroff/O'Reilly
    Year
    2020
    Dimensions
    Dimensions (W x H x D)
    7 x 9 x 0.9 inches

    Table of Contents (9789385889189_toc.pdf, 186 Kb) [Download]

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