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Artificial Intelligence By Example

You're reading from   Artificial Intelligence By Example Develop machine intelligence from scratch using real artificial intelligence use cases

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788990547
Length 490 pages
Edition 1st Edition
Languages
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Author (1):
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Denis Rothman Denis Rothman
Author Profile Icon Denis Rothman
Denis Rothman
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Table of Contents (19) Chapters Close

Preface 1. Become an Adaptive Thinker 2. Think like a Machine FREE CHAPTER 3. Apply Machine Thinking to a Human Problem 4. Become an Unconventional Innovator 5. Manage the Power of Machine Learning and Deep Learning 6. Don't Get Lost in Techniques – Focus on Optimizing Your Solutions 7. When and How to Use Artificial Intelligence 8. Revolutions Designed for Some Corporations and Disruptive Innovations for Small to Large Companies 9. Getting Your Neurons to Work 10. Applying Biomimicking to Artificial Intelligence 11. Conceptual Representation Learning 12. Automated Planning and Scheduling 13. AI and the Internet of Things (IoT) 14. Optimizing Blockchains with AI 15. Cognitive NLP Chatbots 16. Improve the Emotional Intelligence Deficiencies of Chatbots 17. Quantum Computers That Think 18. Answers to the Questions

Defining a CNN

This section describes the basic components of a CNN. 01_CNN_SRATEGY_MODEL.py will illustrate the basic CNN components the chapter used to build the case study model for a food-processing conveyor belt. CNNs constitute one of the pillars of deep learning (multiple layers and neurons).

In this chapter, a Keras neural network written in Python will be running on top of TensorFlow. If you do not have Python or do not wish to program, the chapter is self-contained with graphs and explanations.

Defining a CNN

A convolutional neural network takes an image, for example, and processes it until it can be interpreted.

For example, imagine you have to represent the sun with an ordinary pencil and a piece of paper. It...

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