hands-on lab
Handling Missing Data
Difficulty: Intermediate
Duration: Up to 1 hour
Students: 679
Rating: 4.6/5
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Description
What do you do when there is unknown or missing values in your data?
This lab will walk you through a number of ways to handle missing data including using a default value and building a model to predict the missing data based on other variables that are present in the data set.
Learning Objectives
Upon completion of this lab you will be able to:
- Import data using pandas
- Check for missing values
- Drop rows with missing data
- Replace missing values with default values
- Impute missing values using a prediction model
Intended Audience
This lab is intended for:
- Machine learning engineers
- Anyone interested in evaluating machine learning model performance
Prerequisites
You should possess:
- A basic understanding of Python
Updates
April 8th, 2022 - Updated instructions for clarity
Covered topics
Lab steps
Logging In to the Amazon Web Services Console
Opening the Lab's Jupyter Notebook
Solutions to Handling Missing Data