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Machine Learning/AI Series: Understanding Machine Learning Regression Model

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.

Antony Ross

Antony originally attained a degree in psychology with an emphasis in sport psychology. He began working with athletes and eventually chose to pursue a graduate degree in exercise physiology. He conducted research in muscle physiology while teaching at USC and, subsequently, UCLA.

Custom training workshops are available for this program

Technology training sessions structured around individual or group learning objectives. Learn more about custom training

University IT Technology Training sessions are available to a wide range of participants, including Stanford University staff, faculty, students, and employees of Stanford Hospitals & Clinics, such as Stanford Health Care, Stanford Health Care Tri-Valley, Stanford Medicine Partners, and Stanford Medicine Children's Health.

Additionally, some of these programs are open to interested individuals not affiliated with Stanford, allowing for broader community engagement and learning opportunities.