Context In this notebook we'll apply regression to a classification problem in order to predict the likelihood of getting hired. The target variable that we are predicting is therefore a binary "Yes" or "No" decision called **`Status`** in our Match table. Content The data is pretty straightforward, there's a Candidate table which contains our candidate features and a Match table which tracks whether a candidate was considered for a job, the dates at which that happened and the hiring decision. One candidate can be presented in multiple job offers simultaneously. Acknowledgements Credits: this notebook is highly inspired by : Human Analog's contribution on Kaggle , Susan Li's article 1 , Susan Li's article 2 and this blog . Thank you for sharing !