April 2017
Intermediate to advanced
532 pages
12h 39m
English
book
Machine Learning with Spark - Second Edition
by Rajdeep Dua, Brian O'Neill, Stephen Boesch, Manpreet Singh Ghotra, Nick Pentreath
Content preview from Machine Learning with Spark - Second Edition
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Step size
In SGD, the step size parameter controls how far in the direction of the steepest gradient the algorithm takes a step when updating the model weight vector after each training example. A larger step size might speed up convergence, but a step size that is too large might cause problems with convergence, as good solutions are overshot. The learning rate determines the size of the steps we take to reach a (local or global) minimum. In other words, we follow the direction of the slope of the surface created by the objective function downhill until we reach a valley.
We can see the impact of changing the step size here:
val stepResults = Seq(0.001, 0.01, 0.1, 1.0, 10.0).map { param => val model = trainWithParams(scaledDataCats, 0.0, ...Become 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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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.
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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.