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

Artificial Intelligence and Big Data

In this chapter, we are going to learn what big data is and how big data technologies can be used in the context of artificial intelligence. We will discuss how big data can help accelerate machine learning pipelines. We will also discuss when it is a good idea to use big data techniques and when they are overkill, using some examples to further our understanding. We will learn about the building blocks of a machine learning pipeline that uses big data and the various challenges involved, and we will create an environment in Python to see how it works in practice. By the end of this chapter, we will have covered:

  • Big data basics
  • The three V's of big data
  • Big data as it applies to artificial intelligence and machine learning
  • A machine learning pipeline using big data
  • Apache Hadoop
  • Apache Spark
  • Apache Impala
  • NoSQL databases

Let's begin with the basics of big data.