yeonjun-in / coursera-how_to_win_ds_competition

coursera-how_to_win_ds_competition

week1

Feauture Preprocessing and Generation with Respect to Models

feature preprocessing and generation with respect to models

1. Overview

2. Numeric features

3. Categorical and ordinal features

4. Datetime and coordinates

5. Handling missing values

week2

Exploratory data analysis

Exploratory data analysis

1. Exploratory data analysis

2. Building intuition about the data

3. Exploring anonymized data

4. Visualizations

5. Dataset cleaning and other things to check

EDA examples

1. Springleaf competition EDA I

2. Springleaf competition EDA II

Validation

1. Validation and Overfitting

2. Validation strategies

3. Data splitting strategies

4. Problems occurring during validation

Data Leakage

week3

Metrics Optimization

1. Motivation

2. Regression metrics review I

3. Regression metrics review II

4. Classfication metrics review

5. general approaches for metrics optimization

6. Regression metrics optimization

7. Classification metrics optimization I

8. Classification metrics optimization II