Data Visualization: Insights That Cause Change
Great data insights don’t mean much if the folks controlling change don’t understand them or don’t have the time to pour over columns of data. Enter data visualization; the key to getting data insights to cause change that improves your market performance.

Google BigQuery Public Datasets
Google BigQuery is not only a fantastic tool to analyze data, but it also has a repository of public data, including GDELT world events database, NYC Taxi rides, GitHub archive, Reddit top posts, and more.

SAP Predictive Analytics 2.0: Navigate the Interface
SAP Predictive Analytics 2.0 has two distinct interfaces for automated analytics and expert analytics. In this tutorial, we will review the interface of SAP Predictive Analytics 2.0.

Prismatic Interest Graph [API]: Organize and Recommend Content
Prismatic Interest Graph API provides a set of tools for automatically analyzing unstructured text and annotating it with a variety of tags that are useful for organizing and recommending content.

Making Maps in R with Ryan Peek and Michele Tobias
Today at the Davis R Users’ Group, Ryan Peek and Michele Tobias gave an introduction to making maps in R. Here’s the webcast:

R Training Path
R is the leading open-source programming language in statistics and data science. By taking this guided Training Path, you’ll be a proficient R user in no time. After taking this track, you’ll be able to manipulate and visualize data professionally thanks to R’s most popular packages. You’ll even learn how to create your own dynamic reporting documents.

Bivariate Choropleth Maps: A How-to Guide
“I’m not bivariate, but I am curious.” That quip has been stuck in my mind ever since I overheard it at the 2013 NACIS conference in Greenville, SC. Not only was it perfectly timed after a talk about bivariate mapping, but it rang with a great deal of truth: a lot of folks aren’t creating bivariate maps, but they want to try. While it was just a joke and the person who made it can easily create bivariate maps, most people find them too difficult or mysterious. That’s a real shame because bivariate choropleth maps are incredibly useful and very easy to make. So let’s go ahead and make one!

Introduction to Bayes Theorem with Python
Bayes theorem is what allows us to go from a sampling (or likelihood) distribution and a prior distribution to a posterior distribution.

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