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)
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In this chapter, we first learned about the potential future of chatbots and how they will affect our society as they get better. We then learned about the limitations of current chatbot technology and what the recommended best practices are given the current limitations. We learned about basic chatbot concepts and what the most popular chatbot platforms are.

Finally, we delved deeper into a chatbot platform developed by Google by the name of DialogFlow. We got familiar with this platform by performing a basic exercise and then learning how we can integrate with other backend services using webhooks. We went step by step to understand how to test the chatbot's functionality and make sure it was set up correctly.

In the next chapter, we will jump into another exciting topic and learn how to train sequential data and use it for time series analysis.