# How to Win a Data Science Competition: Learn from Top Kagglers

## Wekk 4

- [[Hyperparameter tuning]]
- [[Hyperparameter tuning I]]

## Week 3

Metrics optimization

- [[Classification metrics review]]
- [[Approaches for target metric optimization]]
- [[Regression metrics optimization]]

## Week 2

- [[Exploratory data analysis]]
- [[Building intuition about the data]]
- [[Reading material for video 2]]
- [[Exploring anonymized data]]
- [[Notebook for video 3 screencast]]
- [[Visualizations]]
- [[Dataset cleaning and other things to check]]
- [[Exploratory data analysis]]
- [[Springleaf competition EDA I]]
- [[Springleaf competition EDA II]]
- [[Numerai competition EDA]]
- [[Validation and overfitting]]
- [[Data splitting strategies]]
- [[Problems occurring during validation]]
- [[Data leakages]]

## Week 1

- [[Welcome to "How to win a data science competition"]]
- [[Competition mechanics]]
- [[Recap of main ML algorithms]]
- [[Software Hardware requirements]]



## 링크

- https://www.coursera.org/learn/competitive-data-science