June 2018
Intermediate to advanced
248 pages
5h 27m
English
Content preview from Mastering Numerical Computing with NumPy
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Summary
Linear regression is one of the most common techniques for modeling the relationship between continuous variables. The application of this method is very widely used in the industry. We started modeling part of the book on linear regression, not just because it's very popular, but because it's a relatively easy technique and contains most of the elements which almost every machine learning algorithm has.
In this chapter, we learned about supervised and unsupervised learning and built a linear regression model by using the Boston housing dataset. We touched upon different important concepts such as hyperparameters, loss functions, and gradient descent. The main purpose of this chapter was to give you sufficient knowledge so that you ...
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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.