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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
Languages
Concepts
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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

Silicon Valley and data science


Several of the key innovations we see today in big data have emerged from Silicon Valley. The region has been a tech hub for decades and has launched some of the most successful companies such as Apple, Google, Facebook, and eBay. The presence of universities, such as the University of California at Berkeley, has made access to talent relatively easy.

That said, the cost of living in the region has sky-rocketed, especially in the wake of the growth of the big data and data science industry. Today, the average rent for a one-bedroom apartment is well above $3,500 per month, making it more expensive than even New York City.

Silicon Valley, however, is synonymous with success and many new entrepreneurs are drawn to the region. Startups have sprung up, many of them commanding tens of millions of dollars in VC investment. However, entrepreneurs should heed statistical warnings given the high failure percentage of startup businesses. It is one thing to have a great...

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