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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

Using TensorBoard to design the architecture of your machine learning and deep learning solutions

FNN_XOR_Tensorflow_tensorbard_graph_only.py contains no program in the traditional sense. It contains an essential aspect of developing machine learning and neural networks: the architecture. This program is overloaded with basic graph summaries to grasp the core concept of the data flow graph. In subsequent programs in this book, the summaries will be less literal.

Master the architecture of a machine learning and deep learning program and you'll master your solutions.

Designing the architecture of the data flow graph

First import TensorFlow with the following code:

import tensorflow as tf

Then use the following code to...

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