November 2017
Beginner to intermediate
366 pages
7h 59m
English
Content preview from R Data Analysis Projects
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Summary
The chapter started with an overview of data at motion and data at rest, also called as the streaming data. We further dwelled into the properties of streaming data and the challenges it poses while processing it. We introduced the stream clustering algorithm. The famous offline/online approach to stream clustering was discussed. Later on, we introduced various classes in stream package and how to use them. During that process, we discussed ideas about several data generators, DBSTREAM algorithms to find micro and macro clusters and several metrics to assess the quality of clusters. We then introduced our use case. We went ahead to design a clustering algorithm, with the online part based on reservoir sampling and the offline part ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.