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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

Product type Paperback

Published in May 2018

Publisher Packt

ISBN-13 9781788472173

Length 384 pages

Edition 1st Edition

Languages

Java

Tools

TensorFlow

Concepts

Artificial Intelligence

Authors (2):

Anand Deshpande

Manish Kumar

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Table of Contents (14) Chapters

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

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MASON Library

Multi-AgentSimulationOfNeighborhoods or Networks (MASON) is a Java-based multi-agent simulation library that has a generic API library in order to easily simulate SI algorithms in particular and any general algorithm that explores the search space with the use of independent agents in general. This library is created by George Mason at the University's Center for Social Complexity and Department of Computer Science. It provides a fast and portable core written in Java programming language and is supported by visualization framework for hypothesis testing and visualization. It is a handy framework for modeling new architectures and algorithms. The design goals for the MASON library are:

Provide a large number of simulations and configurable experiments. The library is very easy to extend for additional simulations and use cases.
High Degree of modularity and flexibility—the framework is built as a layered architecture and it deploys object oriented fundamentals for keeping the...

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Authors (2)

Deshpande

Deshpande

Tanmay Deshpande is a Hadoop and big data evangelist. He currently works with Schlumberger as a Big Data Architect in Pune, India. He has interest in a wide range of technologies, such as Hadoop, Hive, Pig, NoSQL databases, Mahout, Sqoop, Java, cloud computing, and so on. He has vast experience in application development in various domains, such as oil and gas, finance, telecom, manufacturing, security, and retail. He enjoys solving machine-learning problems and spends his time reading anything that he can get his hands on. He has great interest in open source technologies and has been promoting them through his talks. Before Schlumberger, he worked with Symantec, Lumiata, and Infosys. Through his innovative thinking and dynamic leadership, he has successfully completed various projects. He regularly blogs on his website http://hadooptutorials.co.in. You can connect with him on LinkedIn at https://www.linkedin.com/in/deshpandetanmay/. He has also authored Mastering DynamoDB, published in August 2014, DynamoDB Cookbook, published in September 2015, Hadoop Real World Solutions Cookbook-Second Edition, published in March 2016, Hadoop: Data Processing and Modelling, published in August, 2016, and Hadoop Blueprints, published in September 2016, all by Packt Publishing.

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Kumar

Kumar

Ashish Kumar is a seasoned data science professional, a publisher author and a thought leader in the field of data science and machine learning. An IIT Madras graduate and a Young India Fellow, he has around 7 years of experience in implementing and deploying data science and machine learning solutions for challenging industry problems in both hands-on and leadership roles. Natural Language Procession, IoT Analytics, R Shiny product development, Ensemble ML methods etc. are his core areas of expertise. He is fluent in Python and R and teaches a popular ML course at Simplilearn. When not crunching data, Ashish sneaks off to the next hip beach around and enjoys the company of his Kindle. He also trains and mentors data science aspirants and fledgling start-ups.

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