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

Feature Selection and Feature Engineering

Feature selection – also known as variable selection, attribute selection, or variable subset selection – is a method used to select a subset of features (variables, dimensions) from an initial dataset. Feature selection is a key step in the process of building machine learning models and can have a huge impact on the performance of a model. Using correct and relevant features as the input to your model can also reduce the chance of overfitting, because having more relevant features reduces the opportunity of a model to use noisy features that don't add signal as input. Lastly, having less input features decreases the amount of time that it will take to train a model. Learning which features to select is a skill developed by data scientists that usually only comes from months and years of experience and can be more of an art than a science. Feature selection is important because it can:

  • Shorten training times...