DATA 1010: Introduction to Probability, Statistics, and Machine Learning
Resources
Class
- September 5 (linear algebra and
programming) [solutions video]
- September 7 (more linear algebra and
programming) [solutions video]
- September 10 (linear algebra and SVD)
[solutions video]
- September 12 (determinants and matrix
differentiation)
[solutions video]
[jupyter]
- September 14 (machine arithmetic)
[solution]
- September 17 (numerical error) [solution]
- September 19 (pseudorandom number
generators, automatic differentiation) [solution]
- September 21 (gradient descent, review) [solution]
- September 24 (probability spaces)
[solution]
- September 26 (counting and random
variables) [solution]
- September 28 (conditional probability and
independence) [solution]
- October 1 (conditional probability)
[solution]
- October 3 (review)
[solution]
- October 5 (expectation)
[solution]
- October 10 (linearity of expectation)
[solution]
- October 12 (continuous distributions)
[solution]
- October 15 (conditional expectation)
[solution]
- October 17 (more continuous distributions,
Bernoulli and binomial distributions)
[solution]
- October 19 (geometric, Poisson, exponential distributions)
[solution]
- October 22 (multivariate normal distribution)
[solution]
- October 24 (law of large numbers and
CLT) [solution]
- October 26 (CLT and multivariate CLT)
[solution]
- October 29 (Kernel density estimation)
[solution]
- October 31 (Kernel density estimation, review)
[solution]
- November 2 (Nonparametric regression)
[solution]
- November 5 (intro to classification, QDA)
[solution]
- November 7 (classification, LDA, Naive
Bayes) [solution]
- November 9 (logistic regression)
[solution]
- November 12 (support vector classification)
[solution]
- November 14 (kernelization for SVM, neural nets)
- [November 17 – December 10] (neural nets, dimension
reduction, likelihood ratio classification, intro to R,
ggplot2
,
dplyr
, point estimation, confidence intervals, empirical CDF
convergence, maximum likelihood estimation, hypothesis testing)
- December 12 (geographic maps in
ggplot2
,
and logistic regression using caret
)
Homework
- PSet 1 - September 14 (linear algebra, SVD)
- PSet 2 - September 21 (matrix differentiation,
machine arithmetic, PRNGs)
- PSet 3 - September 28 (automatic
differentiation, gradient descent, probability, review problems)
- PSet 4 - October 5 (review problems, probability)
- PSet 5 - October 12 (expectation)
- PSet 6 - October 19 (continuous
distributions, conditional expectation)
- PSet 7 - October 26 [files] (common
distributions, central limit theorem)
- PSet 8 - November 02 (probability review)
- PSet 9 - November 09 (kernel density
estimation, nonparametric regression, classification)
- PSet 10 - November 16 (logistic
regression, support vector machines, neural nets)
- PSet 11 - November 30 (dimension
reduction, likelihood ratio classification, data visualization and
manipulation)
- PSet 12 - December 17 (point estimation,
confidence intervals, bootstrap, and maximum likelihood estimation)
Videos
Exams
Animations
Links