Book Image

Artificial Intelligence with Python - Second Edition

By : Prateek Joshi
Book Image

Artificial Intelligence with Python - Second Edition

By: Prateek Joshi

Overview of this book

Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques.
Table of Contents (26 chapters)
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Natural Language Processing

In this chapter, we will learn about the exciting topic of natural language processing (NLP). As we have discussed in previous chapters, having computers that are able to understand human language is one of the breakthroughs that will truly make computers even more useful. NLP provides the foundation to begin to understand how this might be possible.

We will discuss and use various concepts, such as tokenization, stemming, and lemmatization, to process text. We will then discuss the Bag of Words model and how to use it to classify text. We will see how to use machine learning to analyze the sentiment of a sentence. We will then discuss topic modeling and implement a system to identify topics in a given document.

By the end of this chapter, you will be familiar with the following topics:

  • Installing relevant NLP packages
  • Tokenizing text data
  • Converting words to their base forms using stemming
  • Converting words to their base forms...