Data Science – NC233

Using R to build predictions for UEFA Euro 2020

June 15, 2021 Antoine Rebecq

Last friday, Euro 2020, one of the biggest events in International soccer, was kicked off by the inaugural match between Italy and Turkey (Italy won it 3-0). Euros (short for European Championships) are usually held every 4 years, but because of he-who-must-not-be-named, last year’s edition was postponed to this summer, while keeping the name “Euro 2020” (much like the Tokyo Olympics). 4 5 years ago, for Euro 2016, I basically wanted to try some cool methods based on splines on…

Have you checked your features distributions lately?

April 14, 2021 Antoine Rebecq

tl;dr Trying to debug a poorly performing machine learning model, I discovered that the distribution of one of the features varied from one date to another. I used a simple and neat affine rescaling. This simple quality improvement brought down the model’s prediction error by a factor 8 Data quality trumps any algorithm I was recently working on a cool dataset that looked unusually friendly. It was tidy, neat, interesting… the kind of things that you rarely encounter in the wild!…

Causal Inference cheat sheet for data scientists

April 29, 2020 Antoine Rebecq

Being able to make causal claims is a key business value for any data science team, no matter their size.Quick analytics (in other words, descriptive statistics) are the bread and butter of any good data analyst working on quick cycles with their product team to understand their users. But sometimes some important questions arise that need more precise answers. Business value sometimes means distinguishing what is true insights from what is incidental noise. Insights that will hold up versus temporary marketing…

NC233

Sampling and data tinkering

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Category: Data Science