Introduction to Statistical Learning will explore concepts in statistical modeling, such as when to use certain models, how to tune those models, and if other options will provide certain trade-offs. We will cover Regression, Classification, Trees, Resampling, Unsupervised techniques, and much more!
제공자:
Regression and Classification
콜로라도 대학교 볼더 캠퍼스이 강좌에 대하여
Intro Statistics and Foundational Math
배울 내용
Express why Statistical Learning is important and how it can be used.
Identify the strengths, weaknesses and caveats of different models and choose the most appropriate model for a given statistical problem.
Determine what type of data and problems require supervised vs. unsupervised techniques.
귀하가 습득할 기술
- Statistics
- Data Science
- R Programming
Intro Statistics and Foundational Math
제공자:

콜로라도 대학교 볼더 캠퍼스
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
석사 학위 취득 시작
강의 계획표 - 이 강좌에서 배울 내용
Statistical Learning Introduction
Introduction to overarching and foundational concepts in Statistical Learning.
Accuracy
Exploration into assessing models in different situations. How do we define a "best" model for given data?
Simple Linear Regression
Introduction to Simple Linear Regression, such as when and how to use it.
Multiple Linear Regression
A deep dive into multiple linear regression, a strong and extremely popular technique for a continuous target.
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
이 수료증을 구매하면 무엇을 이용할 수 있나요?
재정 지원을 받을 수 있나요?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.