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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

Building the architecture of an FNN with TensorFlow

Before applying an FNN to a problem, an architecture of the network must be built. A TensorFlow architecture and solution to the XOR function is the place to start. The architecture of the example differs from the vintage, built-from-scratch solution but the concepts remain the same.

Writing code using the data flow graph as an architectural roadmap

TensorFlow is a graph-driven solution based on graph theory, a branch of mathematics. Designing deep learning without graphs would prove quite difficult. My XOR FNN built from scratch in Chapter 4, Become an Unconventional Innovator, fits the need of the case study described. However, if thousands of nodes are required, TensorFlow...

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