Loading...

Logistic Regression

Course video 13 of 35

This module delves into a wider variety of supervised learning methods for both classification and regression, learning about the connection between model complexity and generalization performance, the importance of proper feature scaling, and how to control model complexity by applying techniques like regularization to avoid overfitting. In addition to k-nearest neighbors, this week covers linear regression (least-squares, ridge, lasso, and polynomial regression), logistic regression, support vector machines, the use of cross-validation for model evaluation, and decision trees.

Coursera 소개

세계 최고의 대학교와 교육 기관의 최상위 강사가 가르쳐주는 강좌와 전문 강좌를 듣고 온라인 학위를 취득하세요.

Community
Join a community of 40 million learners from around the world
Certificate
Earn a skill-based course certificate to apply your knowledge
Career
Gain confidence in your skills and further your career