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Machine Learning/AI Series: Understanding Machine Learning Regression Model

Class Sessions

Date Location Cost
  • Mon Apr 26, 3:00 pm to 4:30 pm
Live Online $150
  • Fri Jun 11, 10:30 am to 12:00 pm
Live Online $150

Class Code

ITS-B1904

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. 

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
Because this is an abbreviated session, 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.