Book Image

Artificial Intelligence and Machine Learning Fundamentals

By : Zsolt Nagy
Book Image

Artificial Intelligence and Machine Learning Fundamentals

By: Zsolt Nagy

Overview of this book

Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!
Table of Contents (10 chapters)
Artificial Intelligence and Machine Learning Fundamentals

Introduction to Clustering

In the previous lessons, we dealt with supervised learning algorithms to perform classification and regression. We used training data to train our classification or regression model, and then we validated our model using testing data.

In this lesson, we will perform unsupervised learning by using clustering algorithms.

We may use clustering to analyze data to find certain patterns and create groups. Apart from that, clustering can be used for many purposes:

  • Market segmentation detects the best stocks in the market you should be focusing on fundamentally. We can detect trends, segment customers, or recommend certain products to certain customer types using clustering.

  • In computer vision, image segmentation is performed using clustering, where we find different objects in an image that a computer processes.

  • Clustering can be combined with classification, where clustering may generate a compact representation of multiple features, which can then be fed to a classifier...