Supervised Machine Learning: Regression
Course Features
Duration
11 hours
Delivery Method
Online
Available on
Limited Access
Accessibility
Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Teaching Type
Self Paced
Video Content
11 hours
Course Description
Course Overview
International Faculty
Case Based Learning
Post Course Interactions
Case Studies,Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
What You Will Learn
Differentiate uses and applications of classification and regression in the context of supervised machine learning
Describe and use linear regression models
Use a variety of error metrics to compare and select a linear regression model that best suits your data
Articulate why regularization may help prevent overfitting
Use regularization regressions: Ridge, LASSO, and Elastic net
Target Students
This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Regression techniques in a business setting.
Course Instructors
Mark J Grover
Digital Content Delivery Lead
Miguel Maldonado
Machine Learning Curriculum Developer
Course Reviews
Average Rating Based on 8 reviews
100%