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R for Machine Learning Part 2

R for Machine Learning Part 2 Online

This is a part of the SummeR of LeaRning Series.

We'll cover the basics of machine learning in R. Below are the concepts we'll teach:

Part 1:

  • Machine Learning Basics
  • Train, Validation, and Test Data
  • Features vs Labels

Part 2:

  • Unsupervised Learning
  • Clustering

Part 3:

  • Supervised Learning
  • Classification
  • Regression

Part 4:

  • Model Interpretation
  • AI Bias

 

Prerequisites

You should be familiar with the materials from:

 

Instructor

Albert Lee is an Instructional Designer and Analyst for the Data Science Initiative at the UCSF Library.

Date:
Friday, Jul 8 2022
Time:
11:05am - 12:00pm
Time Zone:
Pacific Time - US & Canada (change)
Campus:
Online
Online:
This is an online event. Event URL will be sent via registration email.
Categories:
  Data Science Initiative > Bioinformatics and Statistics     Data Science Initiative > Programming  
Registration has closed.

Event Organizer

Profile photo of Albert Lee
Albert Lee