Machine Learning/AI Series: Understanding Deployment of Machine Learning Models

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 explore different tools used in deploying machine learning models.

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 who is familiar with machine learning terminology and understands how to build a machine learning model.

Learning Objectives:
Learn about different libraries involved in saving and using a machine learning model. In the hands-on session, we will look at the following:

• How to save a machine learning model
• How to load that model to make predictions on new data

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.