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index.Rmd
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<ul class="navibar">
<li><a href="./index.html" class="current" >Schedule</a></li>
<li><a href="./syllabus.html" class="navibar" >Syllabus</a></li>
<li><a href="./homework.html" class="navibar" >Homework</a></li>
</ul>
<!--- Start Main Page --->
<br><br>
### Schedule
-----------
------------------------------------------------------------------------------------------------
Class Date Day Topic Reading (Pre-Class) Notes from class
----- -------- ----- -------------------------- ----------------------- -----------------------
1 Aug 24 Thu Intro Chap 1 [Streak Betting](https://mdporter.github.io/teaching/streak-betting/streak-betting.html)
2 Aug 29 Tue Supervised Learning 2.1-2.3 02-supervised.pdf handout
3 Aug 31 Thu Supervised Learning 2.4-2.6
4 Sept 5 Tue Supervised Learning 2.7-2.9 02-bias-variance.pdf handout
5 Sept 7 Thu Linear Regression 3.1-3.2 **HW #1 Due** [R Formula Interface](other/03-rfmla.pdf)
6 Sept 12 Tue Subset Selection 3.3 [R Code: subsets](other/03-subsets.R)
7 Sept 14 Thu Shrinkage Methods 3.4 [R Code: ridge](other/03-ridge.R)
8 Sept 19 Tue [Lasso] 3.6 [R Code: lasso](other/03-lasso.R)
9 Sept 21 Thu Algorithms 3.8-3.9
10 Sept 26 Tue **HW #2 Due**
11 Sept 28 Thu Logistic Regression 4.1-4.2; 4.4
12 Oct 3 Tue GLM [Rodriguez Notes]
13 Oct 5 Thu Model Assessment 7.1-7.3; 7.10
14 Oct 10 Tue [Model Assessment] 7.4-7.7; 7.11 <!-- [R Code](R/08-crossval.R) -->
<!--
[Model Selection]
-->
15 Oct 12 Thu Penalized B splines 5.1-5.2; [R Code: B-spline](other/05-bsplines.R)
[Eilers \& Marx]
16 Oct 17 Tue Generalize Additive 5.6, 9.1
Models
<!-- link -->
17 Oct 19 Thu Classification/Pattern **HW #3 Due**
Recognition
18 Oct 24 Tue LDA 4.3
Oct 26 Thu <font color="orange">
*No Class: Fall Break*
</font>
19 Oct 31 Tue [Nonparametric Density 6.6-6.8 <!-- [R Code](R/11-density.R) -->
Estimation]
<!-- [Rmd](lectures/
12-npdensity.Rmd)
-->
20 Nov 2 Thu Naive Bayes; 6.1-6.5
Kernel
Smoothing
21 Nov 7 Tue Bayesian Estimation 8.1-8.4 **HW #4 Due**
and Bootstrap
22 Nov 9 Thu [Trees] 9.2, 8.7-8.9 <!-- [R Code](R/13-trees.R) -->
23 Nov 14 Tue Ensembles \& Random 8.7-8.9, 15
Forests
24 Nov 16 Thu Boosting I 10; <!-- [R Code](R/14-boosting.R) -->
[LogitBoost paper]
25 Nov 21 Tue Boosting II 16
Nov 23 Thu <font color="orange">
*No Class: Thanksgiving
Break*
</font>
26 Nov 28 Tue Anomaly detection I
27 Nov 30 Thu Anomaly detection II <!-- [R Code](R/15-changedetect.R) -->
28 Dec 5 Tue [Networks and Pagerank]
29 Dec 7 Thu Open Topics
------------------------------------------------------------------------------------------------
-----------
[Lasso]: lectures/03-lasso.pdf
[Eilers \& Marx]: other/(eilers-marx) Flexible smoothing.pdf
[Rodriguez Notes]: http://data.princeton.edu/wws509/notes/a2.pdf
[Model Assessment]: lectures/07-modelselection.pdf
[Nonparametric Density Estimation]: lectures/npdensity.pdf
[Trees]: lectures/trees.pdf
[LogitBoost paper]: https://web.stanford.edu/~hastie/Papers/AdditiveLogisticRegression/alr.pdf
[networks and pagerank]: lectures/16-networks.pdf