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A D3 Image Is Worth A Thousand Words: Interview With Morgane Ciot
Editor’s Note: Morgane, Data Robot and ODSC have been working together for a few years bringing Data Science insights and capability to the masses, so if you missed Morgane’s Talk at ODSC EAST 2017 Check out ODSC West 2017’s Visualization Track. Many things have been said... Read more
Intro to D3
Abstract: Visualizations are the most important way we can intuitively make sense of our data. And the best way to dig deeper into our data is to make those visualizations interactive. Everyone from the New York Times to Google is using interactive visualizations to tell stories... Read more
The inspiration for this post is a joint venture by both me and my husband, and its genesis lies more than 15 years in our past. One of the recurring conversations we have in our relationship (all long-term relationships have these, right?!) is about song lyrics... Read more
This is the second article in our two-part series on using unsupervised and supervised machine learning techniques to analyze music data from Pandora and Spotify. Introduction As you may recall from the previous post I did, where I applied dimensionality reduction and clustering techniques to a set of songs... Read more
Last Saturday, in the UEFA Champions League final (think of it as Europe’s Super Bowl), Spanish giants Real Madrid defeated their Italian counterparts Juventus FC 4-1. It was a thrilling match, that saw both sides staking an equal claim to winning the match in the first half, with... Read more
Pandas & Seaborn – A guide to handle & visualize data elegantly
Here at Tryolabs we love Python almost as much as we love machine learning problems. These kind of problems always involve working with large amounts of data which is key to understand before applying any machine learning technique. To understand the data, we need to manipulate... Read more
Regular Expression & Treemaps to Visualize Emergency Department Visits
It’s been a while since my last post on some TB WHO data. A lot has happened since then, including the opportunity to attend the Open Data Science Conference (ODSC) East held in Boston, MA. Over a two day period I had the opportunity to listen to a... Read more
In this post we will describe how to evaluate a predictive model. Why bother creating complex predictive models if 5% of the customers will churn anyway? Because a predictive model will rank our clients based on the probability that they  will abandon the company. It helps answer these... Read more
Drawing a map of distributed data systems
How we created an illustrated guide to help you find your way through the data landscape. Designing Data-Intensive Applications, the book I’ve been working on for four years, is finally finished, and should be available in your favorite bookstore in the next week or two. An... Read more
Choroplethr v3.6.0 is now on CRAN
Choroplethr version 3.6.0 is now on CRAN. This version adds functionality for getting and mapping demographics of US Census Tracts. You can install it from the R console as follows: 1 2 3 install.packages("choroplethr") packageVersion("choroplethr") ‘3.6.0’ To use this functionality you will need an API... Read more