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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

Summary

Up to this point, we have explored Python with NumPy, TensorFlow, sklearn, pandas, and matplotlib libraries. More platforms and libraries will be implemented in this book. In the months and years to come, even more languages, libraries, frameworks, and platforms will appear on the market. However, artificial intelligence is not only about development techniques. It is a branch of applied mathematics that requires a real-life interest in the field to deliver. Building a k-means clustering program from scratch requires careful planning. The program relies on data that is rarely available as we expect it. That's where our imagination comes in handy to find the right features for our datasets.

Once the dataset has been defined, poor conditioning can compromise the project. Some small changes in the data will lead to incorrect results.

Preparing the training dataset from...

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