You're reading from Artificial Intelligence By Example Acquire advanced AI, machine learning, and deep learning design skills

Product type Paperback

Published in Feb 2020

Publisher Packt

ISBN-13 9781839211539

Length 578 pages

Edition 2nd Edition

Languages

Python

Tools

TensorFlow

Concepts

Artificial Intelligence

Author (1):

Denis Rothman

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Table of Contents (23) Chapters

Preface

1. Getting Started with Next-Generation Artificial Intelligence through Reinforcement Learning

2. Building a Reward Matrix – Designing Your Datasets FREE CHAPTER

3. Machine Intelligence – Evaluation Functions and Numerical Convergence

4. Optimizing Your Solutions with K-Means Clustering

5. How to Use Decision Trees to Enhance K-Means Clustering

6. Innovating AI with Google Translate

7. Optimizing Blockchains with Naive Bayes

8. Solving the XOR Problem with a Feedforward Neural Network

9. Abstract Image Classification with Convolutional Neural Networks (CNNs)

10. Conceptual Representation Learning

11. Combining Reinforcement Learning and Deep Learning

12. AI and the Internet of Things (IoT)

13. Visualizing Networks with TensorFlow 2.x and TensorBoard

14. Preparing the Input of Chatbots with Restricted Boltzmann Machines (RBMs) and Principal Component Analysis (PCA)

15. Setting Up a Cognitive NLP UI/CUI Chatbot

16. Improving the Emotional Intelligence Deficiencies of Chatbots

17. Genetic Algorithms in Hybrid Neural Networks

18. Neuromorphic Computing

19. Quantum Computing

20. Answers to the Questions

21. Other Books You May Enjoy

22. Index

Introducing CNNs

This section describes the basic components of a CNN. CNN_SRATEGY_MODEL.py will illustrate the basic CNN components used to build a model for abstract image detection. For machines, as for humans, concepts are the building blocks of cognition. CNNs constitute one of the pillars of deep learning (multiple layers and neurons).

In this chapter, TensorFlow 2 with Python will be running using Keras libraries that are now part of TensorFlow. If you do not have Python or do not wish to follow the programming exercises, the chapter is self-contained, with graphs and explanations.

Defining a CNN

A convolutional neural network processes information, such as an image, for example, and makes sense out of it.

For example, imagine you have to represent the sun with an ordinary pencil and a piece of paper. It is a sunny day, and the sun is shining very brightly—too brightly. You put on a special pair of very dense sunglasses. Now you can...