You're reading from Python Machine Learning by Example Build intelligent systems using Python, TensorFlow 2, PyTorch, and scikit-learn

Product type Paperback

Published in Oct 2020

Publisher Packt

ISBN-13 9781800209718

Length 526 pages

Edition 3rd Edition

Languages

Python

Tools

PyTorch

Concepts

Machine Learning

Author (1):

Yuxi (Hayden) Liu

View More author details

Table of Contents (17) Chapters

Preface

1. Getting Started with Machine Learning and Python

2. Building a Movie Recommendation Engine with Naïve Bayes FREE CHAPTER

3. Recognizing Faces with Support Vector Machine

4. Predicting Online Ad Click-Through with Tree-Based Algorithms

5. Predicting Online Ad Click-Through with Logistic Regression

6. Scaling Up Prediction to Terabyte Click Logs

7. Predicting Stock Prices with Regression Algorithms

8. Predicting Stock Prices with Artificial Neural Networks

9. Mining the 20 Newsgroups Dataset with Text Analysis Techniques

10. Discovering Underlying Topics in the Newsgroups Dataset with Clustering and Topic Modeling

11. Machine Learning Best Practices

12. Categorizing Images of Clothing with Convolutional Neural Networks

13. Making Predictions with Sequences Using Recurrent Neural Networks

14. Making Decisions in Complex Environments with Reinforcement Learning

15. Other Books You May Enjoy

16. Index

Touring popular NLP libraries and picking up NLP basics

Now that we have covered a short list of real-world applications of NLP, we will be touring the essential stack of Python NLP libraries. These packages handle a wide range of NLP tasks as mentioned previously, including sentiment analysis, text classification, and NER.

Installing famous NLP libraries

The most famous NLP libraries in Python include the Natural Language Toolkit (NLTK), spaCy, Gensim, and TextBlob. The scikit-learn library also has impressive NLP-related features. Let's take a look at them in more detail:

nltk: This library (http://www.nltk.org/) was originally developed for educational purposes and is now being widely used in industry as well. It is said that you can't talk about NLP without mentioning NLTK. It is one of the most famous and leading platforms for building Python-based NLP applications. You can install it simply by running the following command...