Machine Learning

Data Preparation for Machine Learning (7-Day Mini-Course)

Last Updated on June 30, 2020

Data Preparation for Machine Learning Crash Course.
Get on top of data preparation with Python in 7 days.

Data preparation involves transforming raw data into a form that is more appropriate for modeling.

Preparing data may be the most important part of a predictive modeling project and the most time-consuming, although it seems to be the least discussed. Instead, the focus is on machine learning algorithms, whose usage and parameterization has become quite routine.

Practical data preparation requires knowledge of data cleaning, feature selection data transforms, dimensionality reduction, and more.

In this crash course, you will discover how you can get started and confidently prepare data for a predictive modeling project with Python in seven days.

This is a big and important post. You might want to bookmark it.

Kick-start your project with my new book Data Preparation for Machine Learning, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.

  • Updated Jun/2020: Changed the target for the horse colic dataset.
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