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‘Implement NLP Use-Cases Using BERT’ by Amandeep


Implement NLP Use-Cases Using BERT

Author: Amandeep

Publisher: BPB Publications

ISBN: 9789390684625

Date: 18- April-2021

No. of Pages: 164

Genre: Artificial Intelligence

Price: £21.99 / $35.95

This book provides a solid foundation for ‘Natural Language Processing’ with pragmatic explanation and implementation of a wide variety of industry wide scenarios. After reading this book, one can simply jump to solve real world problems and join the league of NLP developers.

It starts with the introduction of Natural Language Processing and provides a good explanation of different practical situations which are currently implemented across the globe. Thereafter, it takes a deep dive into the text classification with different types of algorithms to implement the same. Then, it further introduces the second important NLP use case called Named Entity Recognition with its popular algorithm choices. Thereafter, it provides an introduction to a state-of-the-art language model called BERT and its application.

After reading this book, you would be prepared to start picking any NLP applications, have a healthy discussion about the pros and cons of different approaches with other team members, and implement a good NLP model.

Finally, at the end of this book you will connect with all the theoretical discussions with code snippets (Python) which would be helpful to implement into your domain-specific applications.

Amandeep has been working as a technical lead in the field of software development at the time of publishing this book. He has worked for almost eight years in a few of the top MNCs. His interests include coding in Java and Python with an inclination in deep learning. He has worked in numerous data science fields, especially Natural Language Processing. He received his master’s degree with a specialization in Data Analytics from the Birla Institute of Technology and Science, Pilani, and has reviewed a few research papers under ‘IEEE Transactions on Neural Networks and Learning Systems’. He has earned certifications from multiple MOOCs on data science, machine learning, deep learning, image processing, natural language processing, artificial intelligence, algorithms, statistics, mathematics, and related courses.