ATP Tennis machine learning project using tennis domain knowledge for informed feature engineering.

1. Elo calulation as powerful feature for determining player strength

2. Analysis of all-time Elos and all-time records, such as career length

3. Feature engineering and preprocessing

4. Model selection -- logistic regression / random forest regression / neural network. Analysis of model accuracies, coefficients, PCA

Best model: 81% accuracy