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Artificial Intelligence for Big Data

You're reading from   Artificial Intelligence for Big Data Complete guide to automating Big Data solutions using Artificial Intelligence techniques

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788472173
Length 384 pages
Edition 1st Edition
Languages
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Authors (2):
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Anand Deshpande Anand Deshpande
Author Profile Icon Anand Deshpande
Anand Deshpande
Manish Kumar Manish Kumar
Author Profile Icon Manish Kumar
Manish Kumar
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Toc

Table of Contents (14) Chapters Close

Preface 1. Big Data and Artificial Intelligence Systems FREE CHAPTER 2. Ontology for Big Data 3. Learning from Big Data 4. Neural Network for Big Data 5. Deep Big Data Analytics 6. Natural Language Processing 7. Fuzzy Systems 8. Genetic Programming 9. Swarm Intelligence 10. Reinforcement Learning 11. Cyber Security 12. Cognitive Computing 13. Other Books You May Enjoy

Fuzzy logic fundamentals


Let's quickly understand how human interactions are seamless, even with a degree of vagueness within our statements. A statement such as John is tall does not have any indication of John's exact height in inches or centimeters. However, within the context of the conversation, two people communicating with each other can understand and infer from it. Now, consider that this conversation is taking place between two teachers in a school about a second grade student, John. Within this context, the statement John is tall means a certain height and we are really good at understanding and inferring contextual meaning from this vague information. The fundamental concept of fuzzy logic originates from the fact that with an increase in the complexity of the environmental context, our ability to make precise and exact statements about the state diminishes, yet in spite of that, the human brain is capable of drawing precise inferences. Fuzzy logic represents a degree of truth...

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