This course is meant to instill a working knowledge of linear algebra terminology and to lay the foundations of advanced data mining techniques like Principal Component Analysis, Factor Analysis, Collaborative Filtering, Correspondence Analysis, Network Analysis, Support Vector Machines and many more. In order to fully comprehend these important tools and techniques, we will need to understand the language in which they are presented: Linear Algebra. This is NOT a rigorous proof-based mathematics course. It is an intuitive introduction to the most important definitions and concepts that are needed to understand and effectively implement these important data mining methodologies. So that we know how to stir the pile…阅读更多.
Linear Algebra for Data Science with examples in R 中涵盖的技术和工具与 商业分析师 招聘广告中的要求最为相似。
