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)
24
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25
Index

What are Gaussian Mixture Models?

Before we discuss Gaussian Mixture Models (GMMs), let's first understand what a Mixture Model is. A Mixture Model is a type of probability density model where it is assumed that the data is governed by several component distributions. If these distributions are Gaussian, then the model becomes a Gaussian Mixture Model. These component distributions are combined in order to provide a multi-modal density function, which becomes a mixture model.

Let's look at an example to understand how Mixture Models work. We want to model the shopping habits of all the people in South America. One way to do it would be to model the whole continent and fit everything into a single model, but people in different countries shop differently. We therefore need to understand how people in individual countries shop and how they behave.

To get a good representative model, we need to account for all the variations within the continent. In this case, we can use...