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Problem Introduction

All services have two opponent forces fighting each other — user acquisition and user churn. As long as you acquire more than you lose, you are on a good road to success. If you’re not, there is some things you can do:

  1. Have users churn slower

Let us disregard acquiring more users for now, as it is expensive and will only become more expensive as time goes by.

That leaves us with reducing churn. In a data driven company, luckily we know quite a lot about our users, and if we are lucky (and we are in…


According to the StackOverflow 2017 survey - how well can you predict your salary and what does it tell you about how to increase this in the future (from a data guys point of view).

For this analysis I used Python in Jupyter Notebooks to predict prices with a linear model. The code can be found on Github.

Let’s start with finding a good linear model to predict salary. For this I wrote a grid search that iterates over different fractions of the entire data set provided for training the model to counter overfitting.

Robert Offner

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