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所在平台: Udemy |
课程主页: https://www.udemy.com/course/connect-the-dots-factor-analysis/
课程评论：没有评论
课程名称：连接点滴：因子分析 概述：因子分析是一种有助于在许多相关变量中提取出影响单一效应的分析工具。本课程将帮助您理解因子分析及其与线性回归的联系。您将学习主成分分析（PCA）作为因子提取的标准技术，并了解其与机器学习的关系。 课程内容包括： - 理解主成分及其概念 - 特征值和特征向量的定义 - 特征值分解的运用 - 利用主成分进行降维和探索性因子分析 - 在Excel、R和Python中实施PCA - 将PCA应用于解释如苹果公司等科技股的回报 - 查找主成分并使用它们构建回归模型 通过本课程，您将能够有效地使用因子分析来处理复杂的数据集，并掌握相关的统计方法和工具。
Factor analysis helps to cut through the clutter when you have a lot of correlated variables to explain a single effect. This course will help you understand Factor analysis and it's link to linear regression. See how Principal Components Analysis is a cookie cutter technique to solve factor extraction and how it relates to Machine learning. What's covered? Principal Components Analysis Understanding principal componentsEigen values and Eigen vectorsEigenvalue decompositionUsing principal components for dimensionality reduction and exploratory factor analysis. Implementing PCA in Excel, R and Python Apply PCA to explain the returns of a technology stock like AppleFind the principal components and use them to build a regression model
