Live training

Preprocessing Machine Learning Data with Python for Beginners

In this live code-along, you will be introduced to the basics of preparing your data for machine learning. Using past marketing data, you will process numeric and categorical data in order to make predictions about a campaign’s success. After the code-along, you will get access to a solution notebook to use as a future reference!

Tuesday, November 29 @ 11 am ET
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Python

What will I learn?

You will learn how to:
  • Techniques for dealing with missing data
  • Prepare categorical variables for a machine learning model
  • Prepare numeric variables for a machine learning model

What should I prepare?

We will be using DataCamp Workspace. All you need is a DataCamp account. If you need help, read the "Getting Started with Workspace" tutorial (https://bit.ly/3xPdPrX). Note that members of some enterprise groups do not yet have access to use DataCamp Workspace. Create a free DataCamp account with your personal email address to follow along.

Who should attend?

We recommend that you have taken the following course before attending:

  • Supervised Learning with scikit-learn

Presenter Bio

Justin Saddlemyer Headshot

Justin Saddlemyer

Workspace Architect

Justin is a Workspace Architect at DataCamp. He holds a bachelor's degree in psychology from St. Francis Xavier University and a graduate degree in social psychology from VU Amsterdam. In 2016 Justin received a Ph.D. in marketing from KU Leuven.
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