Rasmus Bååth
Senior Data Scientist at King (Activision Blizzard)
I'm a Data Scientist at King (Activision/Blizzard) and previously I've been an instructor at DataCamp. I once did a PhD in Cognitive Science at Lund University. I'm passionate about Bayesian statistics, good graphs and free coffee. Follow me @rabaath on Twitter or check out my blog, Publishable Stuff.
See MoreCollaborator(s)
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Chester Ismay
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Nick Solomon
Prerequisites
Course Description
Bayesian data analysis is an approach to statistical modeling and machine learning that is becoming more and more popular. It provides a uniform framework to build problem specific models that can be used for both statistical inference and for prediction. This course will introduce you to Bayesian data analysis: What it is, how it works, and why it is a useful tool to have in your data science toolbox.
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1
What is Bayesian Data Analysis?
FreeThis chapter will introduce you to Bayesian data analysis and give you a feel for how it works.
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How does Bayesian inference work?
In this chapter we will take a detailed look at the foundations of Bayesian inference.
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Why use Bayesian Data Analysis?
This chapter will show you four reasons why Bayesian data analysis is a useful tool to have in your data science tool belt.
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Bayesian inference with Bayes' theorem
Learn what Bayes theorem is all about and how to use it for statistical inference.
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More parameters, more data, and more Bayes
Learn about using the Normal distribution to analyze continuous data and try out a tool for practical Bayesian analysis in R.
