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Practical Big Data Analytics

You're reading from   Practical Big Data Analytics Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781783554393
Length 412 pages
Edition 1st Edition
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Author (1):
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Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
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Table of Contents (13) Chapters Close

Preface 1. Too Big or Not Too Big FREE CHAPTER 2. Big Data Mining for the Masses 3. The Analytics Toolkit 4. Big Data With Hadoop 5. Big Data Mining with NoSQL 6. Spark for Big Data Analytics 7. An Introduction to Machine Learning Concepts 8. Machine Learning Deep Dive 9. Enterprise Data Science 10. Closing Thoughts on Big Data 11. External Data Science Resources 12. Other Books You May Enjoy

Factors that led to the success of machine learning


Given machine learning, as a subject, has existed for many decades, it begs the question: why hadn't it become as popular as it is today much sooner? Indeed, the theories of complex machine learning algorithms such as neural networks were well known by the late 1990s, and the foundation had been established well before that in the theoretical realm.

There are a few factors that can be attributed to the success of machine learning:

  • The Internet: The web played a critical role in democratizing information and connecting people in an unprecedented way. It made the exchange of information simple in a way that could not have been achieved through the pre-existing methods of print media communication. Not only did the web transform and revolutionize the dissemination of information, it also opened up new opportunities. Google's PageRank, as mentioned earlier, was one of the first large-scale and highly visible successes in the application of statistical...
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