Live Training

Market Basket Analysis in Python

Join us for this live, hands-on training where you will learn how to analyze consumer behavior in Python with simple, but powerful algorithms. Using Jupyter Notebooks you’ll learn how to translate vast amounts of consumer decision-making data into concrete recommendations for businesses by applying Market Basket Analysis. This session will run for three hours, allowing you time to really immerse yourself in the subject, and includes short breaks and opportunities to ask the expert questions throughout the training.

What will I learn?

You will learn how to:

  • Identify patterns in consumer decision-making with the mlxtend package.
  • Use metrics to evaluate the properties of patterns.
  • Construct "rules" that provide concrete recommendations for businesses.
  • Visualize patterns and rules using seaborn and matplotlib.

What should I prepare?

Please note, a Gmail account is required in order to use Colaboratory, a free Jupyter notebook environment. You can join the webinar from your web browser following the instructions you receive in your registration email. All required data/resources will be provided in the training.

Who should attend?

This course is open to all DataCamp Premium learners, looking to analyze consumer behavior with simple, but powerful techniques in Python. We recommend that you have taken the following course before attending:

Market Basket Analysis with Python
Isaiah Hull

Economist

Isaiah Hull is a Senior Economist at Sweden's Central Bank and holds a PhD in Economics from Boston College. His research is centered around computational economics and machine learning applications in economics. In addition to this research, he is currently working on an interdisciplinary project to introduce quantum technology to economists and a textbook about machine learning for economics and finance.

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