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Machine Learning/AI Series: Understanding Machine Learning Regression Model

Class Code

ITS-1944

Class Description

Effective immediately in response to COVID-19, most 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 session intended to get you started with applying linear regression algorithm to build a machine learning model.

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

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

Objectives:
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.

Setup
Attendees must install Anaconda software (https://www.anaconda.com/) 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.