Machine Learning with Python: Association Rules/ with Frederick Nwanganga.

Format:

Video

Author/Creator:

Nwanganga, Frederick, speaker.

Contributor:

linkedin.com (Firm)

Language:

English

Genre:

Instructional films.

Educational films.

Physical Description:

1 online resource

Place of Publication:

Carpenteria, CA: linkedin.com, 2022.

System Details:

Latest version of the following browsers: Chrome, Safari, Firefox, or Internet Explorer. Adobe Flash Player Plugin. JavaScript and cookies must be enabled. A broadband Internet connection.

Summary:

Explore the unsupervised machine learning approach known as association rules, as well as a step-by-step guide on how to use the approach for market basket analysis in Python.

Join instructor Frederick Nwanganga as he introduces a practical, easy-to-understand approach to using machine learning to solve real-world problems and provides step-by-step guidance on how to do this in Python. Frederick focuses specifically on association rules and how you can apply them for market basket analysis. He explains what association rules are and goes over two popular algorithms, then dives into when and why you should use association rules. Plus, Frederick covers how to create, visualize, and interpret association rules in Python. This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time-all while using a tool that you'll likely encounter in the workplace. Check out the "Using GitHub Codespaces with this course" video to learn how to get started.

Participant:

Presenter: Frederick Nwanganga

Notes:

11/09/2022

Access Restriction:

Restricted for use by site license.