Course Information. This course is open to graduates and senior undergraduates in applied mathematics, statistics, and engineering, who are interested in learning from data. Students with other backgrounds such as life sciences are also welcome, provided you have certain maturity of mathematics. It will cover wide topics in geometric principal component analysis and manifold learning, etc.
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Fall , also offered on Spring and Fall Jiayi Liu, email: liu at purdue. Lecture 2 : probability review joint, marginal and conditional probabilities. Lecture 3 : statistics review independence, maximum likelihood estimation. Lecture 4 : linear algebra review iClicker: attendance. Linear algebra in Python Homework 1 : due on Sep 5, at end of lecture.
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We have a data table with 4 rows and 10 independent variables. Without performing the PCA, do we have an idea of the shape of the correlation circle obtained? Simulate and comment. You can increase the number of rows, also look at cases with 10 rows and variables, etc..
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