Note: The timeline of topics and assignments might be updated throughout the semester.
| 1 |
15 April |
Course Intro, Ch 1 - Stat Learning Examples, Ch 2 - SL, Bias-Variance Tradeoff |
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| 2 |
16 April |
Ch 5 - Cross Validation, Tidy Models |
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| 3 |
17 April |
Ch 5 - Cross Validation, Tidy Models, Ch 3 - LR |
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| 4 |
18 April |
Ch 4 - Logistic Regression |
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| 5 |
19 April |
Ch 4 - LDA, QDA |
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| 6 |
22 April |
Ch 4 - Naive Bayes, KMeans Classification |
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| 7 |
23 April |
Ch 6 - Subset Selection |
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| 8 |
24 April |
Ch 6 - Shrinkage Methods |
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| 9 |
25 April |
Tidymodel recipies |
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| 10 |
26 April |
Exam |
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| 11 |
29 April |
Ch 6 - Dimension Reduction, project |
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| 12 |
30 April |
Ch 8 - Decision Trees, project |
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| 13 |
1 May |
Ch 8 - Bagging, RF, Boosting, project |
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| 14 |
2 May |
Ch 8 - Bagging, RF, Boosting, project |
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| 15 |
3 May |
Ch 8 - Bagging, RF, Boosting, project |
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| 16 |
6 May |
Ch 12 - PCA or Clustering, project |
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| 17 |
7 May |
Finish Up, watch project videos, surveys etc |
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| 18 |
8 May |
Exam |
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