September 2015
Beginner to intermediate
608 pages
13h 43m
English
Content preview from Clojure for Data ScienceBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Summary
In this chapter, we've learned about graphs: a useful abstraction to model a huge variety of phenomena. We started the chapter using the Clojure library Loom to visualize and traverse small graphs of Twitter followers. We learned about two different methods of graph traversal, depth-first and breadth-first search, and the effect of changing edge weights on the paths discovered by Dijkstra's algorithm and Prim's algorithm. We also looked at the density of the whole graph and plotted the degree distributions to observe the difference between random and scale-free graphs.
We introduced GraphX and the Clojure library Glittering as a means of processing large graphs in a scalable way using Spark. In addition to providing several built-in graph ...
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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.