Keynote | Stacking Models for High Performance Machine Learning
10:20 - 11:00
Stacking model is a proven strategy to achieve high accuracy in machine learning solutions. At first glance, the idea behind stacking looks simple, but there are many pitfalls that can lead a wining solution to become a complete disaster when predicting new data. Techniques, tips and tricks on how to stack models, architectures, cross-validation, feature engineering, training algorithms, hyperparameter tuning and previous Kaggle top solutions will be presented and explored.