Practical Big Data Analytics
Big Data analytics relates to the strategies used by enterprises to process and analyze large amounts of data to bring out hidden insights. With the help of open source and enterprise tools, such as R, Python, Hadoop, and Spark, you will learn how to effectively mine your Big Data. By the end of this book, you will have a clear understanding of how you can develop your own Big Data analytics solutions using different tools and methods.
Offered by
Difficulty Level
Intermediate
Completion Time
13h44m
Language
English
About Book
Who Is This Book For?
The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.
Practical Big Data Analytics
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 13h44m total length
Too Big Or Not Too Big
Big Data Mining For The Masses
The Analytics Toolkit
Big Data with Hadoop
Big Data Mining with NoSQL
Spark for Big Data Analytics
An Introduction to Machine Learning Concepts
Machine Learning Deep Dive
Enterprise Data Science
Closing thoughts on Big Data
Appendix- External Data Science Resources
Related Resources
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