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

Deep Learning with Convolutional Neural Networks

In this chapter, we are going to learn about deep learning and Convolutional Neural Networks (CNNs). CNNs have gained a lot of momentum over the last few years, especially in the field of image recognition. We will talk about the architecture of CNNs and the type of layers used inside. We are going to see how to use a package called TensorFlow. We will build a perceptron-based linear regressor. We are going to learn how to build an image classifier using a single-layer neural network.

We will then build an image classifier using a CNN. Image classifiers have many applications. It's a fancy name, but it's just the ability of computers to discern what an object is. For example, you might build a classifier that determines if something is a hotdog or not a hotdog. This is a lighthearted example, but image classifiers can also have life-or-death applications. Picture a drone that has image classification software embedded...