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

Sequential Data and Time Series Analysis

In this chapter, we are going to learn how to build sequence learning models. In order to do this, we will cover a number of topics to give us a good grasp of how to build and use these models. We will learn how to handle time series data in Pandas. We will gain an understanding of how to slice time series data and perform various operations on it and then we will discuss how to extract various statistics from time series data on a rolling basis. Following that, we will learn about Hidden Markov Models (HMM) and then implement a system to build those models. We will gain an understanding of how to use Conditional Random Fields to analyze sequences of alphabets, and finally we will discuss how to analyze stock market data using the techniques learned so far.

By the end of this chapter, you will have covered:

  • Understanding sequential data
  • Handling time series data with Pandas
  • Slicing time series data
  • Operating on time series...