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Machine Learning/AI Series: Understanding Machine Learning Regression Model

Class Code


Class Description

Effective immediately in response to COVID-19, all Technology Training classes will be delivered online until further notice.

In advance of each session, Tech Training will provide you with a Zoom link to your class, along with any required class materials.

A byte-sized session intended to get you started with applying linear regression algorithm to build a machine learning model.

Part of the Machine Learning / Artificial Intelligence Class Series. Optional: Attend 4 out of the 6 sessions and work towards obtaining a Technology Training ML/AI Proficiency Certification. 

Have a basic understanding of Python language, Pandas library, and be familiar with how to use Jupyter Notebook.

This session is designed for anyone familiar with the basic steps involved in machine learning and the tools involved in building machine learning models.

Learn about the intuition about Linear Regression algorithm in machine learning for Univariate and Multi-variate data. We will then build a linear regression algorithm to do the following:

  • Build a model on a dataset.
  • Look at different metrics involved in looking at the performance of the model.

Because this is an abbreviated session, attendees MUST install Anaconda software ( prior to the class, and have a basic understanding of using Jupyter Notebook.

University IT Technology Training classes are only available to Stanford University staff, faculty, students and Stanford Hospitals & Clinics employees. A valid SUNet ID is needed in order to enroll in a class.