Advanced Linear Models for Data Science 1: Least Squares

开始时间: 02/27/2021 持续时间: Unknown

所在平台: Coursera

课程类别: 其他类别

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/linear-models

Explore 1600+ online courses from top universities. Join Coursera today to learn data science, programming, business strategy, and more.

课程评论:没有评论

第一个写评论        关注课程

课程详情

Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: - A basic understanding of linear algebra and multivariate calculus. - A basic understanding of statistics and regression models. - At least a little familiarity with proof based mathematics. - Basic knowledge of the R programming language. After taking this course, students will have a firm foundation in a linear algebraic treatment of regression modeling. This will greatly augment applied data scientists' general understanding of regression models.

数据科学1:最小二乘的高级线性模型:欢迎使用数据科学1:最小二乘的高级线性模型。该课程从线性代数和数学的角度介绍最小二乘。在开始上课之前,请确保您具有以下条件: -基本了解线性代数和多元演算。 -基本了解统计和回归模型。 -至少对基于证明的数学有所了解。 -R编程语言的基本知识。 学习完本课程后,学生将为回归建模的线性代数处理打下坚实的基础。这将大大增强应用数据科学家对回归模型的一般理解。

课程大纲

We cover some basic matrix algebra results that we will need throughout the class. This includes some basic vector derivatives. In addition, we cover some some basic uses of matrices to create summary statistics from data. This includes calculating and subtracting means from observations (centering) as well as calculating the variance.

课程评论(0条)

Coursera Plus banner featuring three learners and university partner logos

课程简介

Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an intr

课程标签

0人关注该课程

主题相关的课程