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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

Introduction to the Weka framework


One of the handy tools in evaluating various data science algorithms is Weka (Waikato Environment for Knowledge Analysis). This is a suite of machine learning software written in the Java programming language. Weka is very popular since it can be extended to leverage additional algorithms and data mining techniques. In this section, we will be introduced to the generic concepts of Weka and specifically look at using it for the implementation of genetic algorithms. 

Weka provides a great and intuitive visual user interface for data mining, analysis, and predictive modeling. Some of the features that make Weka a popular choice for the community are the following:

  • Weka is available as a free tool to use under the GNU General Public license
  • Weka is written in the Java programming language and compiles to byte code, which is easily portable across platforms
  • Weka contains a rich library of machine learning algorithms and it can further be extended within the framework...
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