| Th 1/20 |
Introduction |
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| Tu 1/25 |
Basic probability |
M4D Chapter 1.1 - 1.2 |
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| Th 1/27 |
Conditional Probability |
M4D Chapter 1.2 |
HW 1, Due Tu 2/22
hippocampus data |
| Tu 2/1 |
Conditional Probability, cont.
ExampleSolutions.ipynb |
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|
| Th 2/3 |
Bayes’ Rule |
M4D 1.6 - 1.8 |
|
| Tu 2/8 |
Classification and Naive Bayes
Probability Cheat Sheet! |
Naive Bayes Wikipedia |
|
| Th 2/10 |
Naive Bayes, cont.
SimpleDataPlots.ipynb
Quiz 1 |
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|
| Tu 2/15 |
Linear Algebra Basics: Vectors |
M4D Chapter 3
Extra: UCD Notes, Sec 5, 15, 16 |
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| Th 2/17 |
K-means Clustering, Nearest Neighbor |
M4D Chapter 8.1 - 8.3
Extra: M4D Chapter 4 |
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| Tu 2/22 |
Maximum Likelihood Estimation |
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HW 1 Due |
| Th 2/24 |
Bayesian Estimation |
|
|
| Tu 3/1 |
Hypothesis Testing: Fisher Exact Test |
Extra: How vaccine trials work |
HW 2, Due Th 3/24
traffic.csv
cardiac.csv |
| Th 3/3 |
Linear Regression |
M4D Section 5.1 |
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| Tu 3/8 |
Spring Break – no class |
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|
| Th 3/10 |
Spring Break – no class |
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|
| Tu 3/15 |
Linear Algebra Basics: Matrices |
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|
| Th 3/17 |
Multiple Linear Regression
MultipleLinearRegression.ipynb
Quiz 2 |
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| Tu 3/22 |
Multiple Linear Regression cont. |
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|
| Th 3/24 |
Singular Value Decomposition (SVD)
SVD.ipynb |
M4D Chapter 7 (through 7.2)
Wikipedia |
HW 3, Due Th 4/7
life_expectancy.csv
HW 2 Due |
| Tu 3/29 |
Principal Component Analysis |
M4D Finish Chapter 7
PCA on Wikipedia |
|
| Th 3/31 |
Canonical Correlation Analysis
CCA.ipynb |
CCA on Wikipedia |
|
| Tu 4/5 |
Logistic Regression |
Logistic Regression on Wikipedia |
|
| Th 4/7 |
Logistic Regression, cont. |
|
HW 4, Due Th 4/21
all-hands.dat
HW 3 Due |
| Tu 4/12 |
Intro to Neural Networks: Perceptron
Quiz 3 |
M4D Chapter 9 - 9.2 |
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| Th 4/14 |
Backpropagation |
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| Tu 4/19 |
Convolution |
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| Th 4/21 |
Convolution, cont. |
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HW 5, Due Wed 5/11
Python code for loading CIFAR-10
HW 4 Due |
| Tu 4/26 |
Generative Models |
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| Th 4/28 |
AutoEncoders / Variational AutoEncoders |
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| Tu 5/3 |
TBA
Quiz 4 |
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