Python Natural Language Processing (NLP) Exercises : From Basics to BERT

by Joshua K. Cage

Thank you for picking up this book. This book is an introduction to Natural Language Processing for python beginners. The book covers 92 real-world problems that show you how to write amazing software from scratch using natural language processing and deep learning. By following the steps in this book, you will be able to create your own software that uses the neural machine translation technology used in the famous Google Translate. To get started with this book, there are only two things you will need 1) the desire to understand how the source code works by modifying it yourself based on a hypothesis 2) Basic python grammar knowledge of Python at the level of reading and writing. The author is currently engaged in research and development of machine learning and natural language processing at a global research institute on planet. Originally, This book starts with the basics of "natural language processing" and builds on the little things to get to the heart of the technology. It then attempts to catch up with the world standards by expanding on the problems using BERT and DistilBERT, which shook up the natural language processing community in 2018, and distilled from it. Table of Contents Chapter 1: Text Processing Chapter 2: UNIX Commands and pandas Chapter 3: Regular Expressions Chapter 4 Word Vectors Chapter 5: Machine Learning(Preprocessing) Chapter 6: Machine Learning(Logistic Regression/RandomForest/SVM/KNN) Chapter 7: Deep Learning(BERT/DistilBERT) Chapter 8: Neural Machine Translation (NMT) Part 1 Chapter 9: Neural Machine Translation (NMT) Part 2

212 pages, Kindle Edition

Published October 3, 2020