CS/DSA 5970: Machine Learning Practice

Note: schedule and readings are subject to change.

HOML = Hands-On Machine Learning

Class # Date Topic Reading Assignment Due
1 Tue, Aug 20 Class Introduction
Taxonomy of Machine Learning Methods
Syllabus
2 Thu, Aug 22 Computing Environment and Python Basics HOML CH 1
3 Tue, Aug 27 Python Basics II TBD HW0
4 Thu, Aug 29 Representing Data I: Pandas and Numpy HOML CH 2
5 Tue, Sep 3 Representing Data II: Statistics and Visualization cont HW 1 HW0
6 Thu, Sep 5 Representing Data III: Pipelines and Transformations cont
7 Tue, Sep 10 Classifiers I HOML CH 3 HW 2 HW 1
8 Thu, Sep 12 Classifiers II cont
9 Tue, Sep 17 Feature Importance cont HW3 HW 2
10 Thu, Sep 19 Linear Regression I HOML CH 4 (pp. 105-110)
11 Tue, Sep 24 Linear Regression II: Gradient Methods cont pp. 111-121 HW 4 HW3
12 Thu, Sep 26 Polynomial Regression cont pp. 121-127
13 Tue, Oct 1 Overfitting and Regularization cont pp. 127-134 HW 5 HW4
14 Thu, Oct 3 Cross-Validation Splitting data sets (focus on the high-level view)
15 Tue, Oct 8 Hyperparameter Selection TBD HW 6 HW 5
16 Thu, Oct 10 Formally Comparing Models TBD
17 Tue, Oct 15 Logistic Regression HOML CH4, pp. 134-142
18 Thu, Oct 17 Support Vector Machines HOML CH 5 HW 7 HW 6
19 Tue, Oct 22 Support Vector Machines cont
20 Thu, Oct 24 Decision Trees: Basics HOML CH 6
21 Tue, Oct 29 Decision Trees: Regression cont HW 8 HW 7
22 Thu, Oct 31 Decision Trees: Ensemble Methods HOML CH 7
23 Tue, Nov 5 Decision Trees: Random Forests cont HW 9
24 Thu, Nov 7 Decision Trees: Boosting cont HW 8
25 Tue, Nov 12 Principal Component Analysis
Kernel PCA
HOML CH 8 HW 10 HW 9
26 Thu, Nov 14 Local Linear Embedding cont
27 Tue, Nov 19 Multidimensional Scaling cont HW 11 HW 10
28 Thu, Nov 21 ISOmap cont
29 Tue, Nov 26 Unsupervised Learning: K-Means Clustering TBD HW 12 HW 11
- - Thanksgiving Holiday
30 Tue, Dec 3 Semi-Supervised Learning TBD
31 Thu, Dec 5 Clustering: Gaussian Mixture Models TBD HW 12


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