04 Data Preparation

Preparation

Chapter 2, page 60-87.

Material

Lecture 4 - Empty

Lecture 4

Python | Visualize missing values

Examples.ipynb

Bag of Words.ipynb

jokes.json

Preparing data.ipynb

Session Description

This lecture will cover the basics of how to prepare a data set for machine learning.

Learning Objectives

• Know how to approach features and when to drop and/or engineer them for your specific purposes
• Prepare a dataset for ML. Specifically, you should be able to explain and perform each of the operations below:
• Handle missing values/NaN-values in appropriate ways
• Identify and handle outliers, inlcuding using a boxplot
• Create dummy variables
• Scale/normalize variables
• Create a bag-of-words-representation for text-data