To quickly improve the quality of your models, you're in the right place! you will accelerate your machine-learning expertise by learning how to:
- tackle data types often found in real-world datasets (missing values, categorical variables),
- design pipelines to improve the quality of your machine-learning code,
- use advanced techniques for model validation (cross-validation),
- build state-of-the-art models that are widely used to win Kaggle competitions (XGBoost), and
- avoid common and essential data science mistakes (leakage).