Book Image

Artificial Intelligence with Python - Second Edition

By : Alberto Artasanchez, Prateek Joshi
Book Image

Artificial Intelligence with Python - Second Edition

By: Alberto Artasanchez, 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

Classification and Regression Using Supervised Learning

In this chapter, we are going to learn about classification and regression of data using supervised learning techniques. By the end of this chapter, you will have a better understanding of these topics:

  • Differences between supervised and unsupervised learning
  • Classification methods
  • Data preprocessing methods
  • Label encoding
  • Logistic regression classifiers
  • The Naïve Bayes classifier
  • Confusion matrixes
  • Support Vector Machines and SVM classifiers
  • Linear and polynomial regression
  • Single-variable and multivariable linear regressors
  • Estimating housing prices using Support Vector Regressors