# ML crash course - Numerical data

> Machine learning crash course 중 Numerical data 챕터

[Machine learning crash course](https://wiki.g15e.com/pages/Machine%20learning%20crash%20course.txt) 중 [Numerical data](https://wiki.g15e.com/pages/Numerical%20data.txt) 챕터

https://developers.google.com/machine-learning/crash-course/numerical-data

## Introduction

## How a model ingests data using feature vectors

## First steps

### Visualize your data

### Statistically evaluate your data

### Find outliers

## Programming exercises

https://developers.google.com/machine-learning/crash-course/numerical-data/programming-exercises

## Normalization

### Linear scaling

### Z-score scaling

### Log scaling

### Clipping

### Summary of normalization techniques

## Binning

### Binning example: number of shoppers versus temperature

### Quantile Bucketing

## Scrubbing

## Qualities of good numerical features

### Clearly named

### Checked or tested before training

### Sensible

## Polynomial transforms

## Conclusion

## What's next

- [ML crash course - Categorical data](https://wiki.g15e.com/pages/ML%20crash%20course%20-%20Categorical%20data.txt)