Lecture 00: Review on
probability and statistics
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Lecture 01: Robust
two-sample test
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Lecture 02: CDF and EDF
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Lecture 03: Permutation
test
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Lecture 04: Contingency
table
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Lecture 05: Survival
analysis
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- Major update:
Discrete and continuous hazard and Greenwood formula.
Lecture 06: Density
estimation
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- Major update:
Multivariate KDE, conditional KDE, and sampling from KDE.
Lecture 07: Regression
analysis
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- Major update:
General basis approach and neural nets.
Lecture 08: Classification
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- Major update: Restructure contents and
add a general logistic regression model.
Lecture 09: Empirical risk
minimization and concentration
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- Major update: Merge ERM and concentration
inequalities.
Accessible HTML is generated by converting the PDF to HTML via pandoc. Gemini AI wrote a simple script for me to run this conversion. See this page for introduction.
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