May 2018
Beginner to intermediate
364 pages
7h 43m
English
Content preview from Hands-On Data Science with Anaconda
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Summary
In this chapter, we have discussed predictive data analytics, modeling and validation, some useful datasets, time series analytics, how to predict future events, seasonality, and how to visualize our data. For Python packages, we have mentioned prsklearn and catwalk. For R packages, we have discussed datarobot, LiblineaR, andeclust. For Julia packages, we explained EQuantEcon. For Octave, we have explained ltfat.
In the next chapter, we will discuss Anaconda Cloud. Some topics include the Jupyter Notebook in depth, different formats of the Jupyter Notebooks, how to share notebooks with your partners, how to share different projects over different platforms, how to share your working environments, and how to replicate others' environments ...
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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.