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

Author :

Sowmya Vajjala

Publisher:

Shroff/O'Reilly

Rs1900

Availability: Available

Shipping-Time: Usually Ships 5-9 Days

    

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Publisher

Shroff/O'Reilly

Publication Year 2020
ISBN-13

9789385889189

ISBN-10 9385889184
Binding

Paperback

Number of Pages 456 Pages
Language (English)
Dimensions (Cms) 20X14X4
Weight (grms) 700

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.

Sowmya Vajjala

Sowmya Vajjala is a Research Officer - Digital Technologies at National Research Council Canada, working in the Multilingual Text Processing group. She is an Experienced Data Scientist and NLP researcher, with expertise in: - rapid prototyping of Natural Language processing solutions in software engineering environments - applying Machine learning and Deep Learning for text classification, natural language generation, Multi lingual language processing - linguistic analysis and statistical modeling of large collections of text data - Information retrieval/extraction, custom search engine development - Teaching programming, NLP and data science to under grad & graduate students from various backgrounds - grant writing for fund raising, and communicating complex technical ideas to a wide spectrum of audience.
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