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Artificial Intelligence with Python

You're reading from   Artificial Intelligence with Python Your complete guide to building intelligent apps using Python 3.x

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Product type Paperback
Published in Jan 2020
Publisher Packt
ISBN-13 9781839219535
Length 618 pages
Edition 2nd Edition
Languages
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Authors (2):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
Alberto Artasanchez Alberto Artasanchez
Author Profile Icon Alberto Artasanchez
Alberto Artasanchez
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Toc

Table of Contents (26) Chapters Close

Preface 1. Introduction to Artificial Intelligence 2. Fundamental Use Cases for Artificial Intelligence FREE CHAPTER 3. Machine Learning Pipelines 4. Feature Selection and Feature Engineering 5. Classification and Regression Using Supervised Learning 6. Predictive Analytics with Ensemble Learning 7. Detecting Patterns with Unsupervised Learning 8. Building Recommender Systems 9. Logic Programming 10. Heuristic Search Techniques 11. Genetic Algorithms and Genetic Programming 12. Artificial Intelligence on the Cloud 13. Building Games with Artificial Intelligence 14. Building a Speech Recognizer 15. Natural Language Processing 16. Chatbots 17. Sequential Data and Time Series Analysis 18. Image Recognition 19. Neural Networks 20. Deep Learning with Convolutional Neural Networks 21. Recurrent Neural Networks and Other Deep Learning Models 22. Creating Intelligent Agents with Reinforcement Learning 23. Artificial Intelligence and Big Data 24. Other Books You May Enjoy
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...

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