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!
Regression and Classification
科罗拉多大学波德分校课程信息
Intro Statistics and Foundational Math
您将学到的内容有
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.
您将获得的技能
- Statistics
- Data Science
- R Programming
Intro Statistics and Foundational Math
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科罗拉多大学波德分校
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.
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授课大纲 - 您将从这门课程中学到什么
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.
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