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學生對 约翰霍普金斯大学 提供的 Modeling Data in the Tidyverse 的評價和反饋

課程概述

Developing insights about your organization, business, or research project depends on effective modeling and analysis of the data you collect. Building effective models requires understanding the different types of questions you can ask and how to map those questions to your data. Different modeling approaches can be chosen to detect interesting patterns in the data and identify hidden relationships. This course covers the types of questions you can ask of data and the various modeling approaches that you can apply. Topics covered include hypothesis testing, linear regression, nonlinear modeling, and machine learning. With this collection of tools at your disposal, as well as the techniques learned in the other courses in this specialization, you will be able to make key discoveries from your data for improving decision-making throughout your organization. In this specialization we assume familiarity with the R programming language. If you are not yet familiar with R, we suggest you first complete R Programming before returning to complete this course....
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1 - Modeling Data in the Tidyverse 的 2 個評論(共 2 個)

創建者 Glenn

2021年2月18日

Pretty decent course that goes through the crucial aspects of the tidymodels workflow. Good for anyone who wants to transition from caret to tidymodels for machine learning. This seems like a relatively new course though, so you might have to wait awhile for enough peers to review.

創建者 Stefan M

2021年10月2日

Well presented and clearly understandable course.