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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 FREE CHAPTER 2. Think like a Machine 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

The XOR limit of the original perceptron

Once the feedforward network for solving the XOR problem is built, it will be applied to a material optimization business case. The material-optimizing solution will choose the best combinations of dimensions among billions to minimize the use of a material with the generalization of the XOR function. First, a solution to the XOR limitation of a perceptron must be fully clarified.

XOR and linearly separable models

In the academic world, like the private world, competition exists. Such a situation took place in 1969. Minsky and Papert published Perceptrons. They proved mathematically that a perceptron could not solve an XOR function. Fortunately, today the perceptron and its neocognitron...

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