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You have completed Introduction to Big Data!
You have completed Introduction to Big Data!
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How do you get insight on all this data?
Learn More
- Apache Hadoop homepage
- Wikipedia has a great history of the Hadoop project and much of the Big Data ecosystem that formed on top of Hadoop
- Apache Spark homepage
- Apache Spark Documentation
- Apache Solr Quickstart
- Apache Lucene homepage
- Elasticsearch in 5 minutes
- Getting started with Tensorflow
- Getting started with Scikit-Learn
- Machine Learning on Spark with MLlib
- More ML on Spark Tutorial
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Let's discuss three of the main
computational use cases for big data.
0:00
When we talk about
generalized data processing,
0:03
we're talking about being fed data and
running a computation over it.
0:06
It's typically fed through a stream,
and the processing could be simple
0:10
as counting, taking the variance of data,
or some other custom algorithm.
0:13
Generalized data processing
forms the foundation
0:18
of most what of you'll encounter if you
work with big data systems and problems.
0:21
These systems provide APIs, or
application programming interfaces,
0:26
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