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R for Machine Learning Part 1 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:
- R for Everyone
- R for Data Manipulation
Instructor
Albert Lee is an Instructional Designer and Analyst for the Data Science Initiative at the UCSF Library.
- Date:
- Friday, Jul 1 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 > Bioinformatics and Statistics Data Science > Programming
Registration has closed.
Albert Lee