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figs
01-Intro-to-Python.ipynb
01-Intro-to-Python.pdf
02A-Getting-Started.ipynb
02A-Getting-Started.pdf
02B-Pandas.ipynb
02B-Pandas.pdf
03-Probability-and-Statistics-Refresher.ipynb
03-Probability-and-Statistics-Refresher.pdf
04-Linear-Algebra-Refresher.ipynb
04-Linear-Algebra-Refresher.pdf
05-Distances-Timeseries.ipynb
05-Distances-Timeseries.pdf
06A-Clustering-Overview.ipynb
06A-Clustering-Overview.pdf
06B-Kmeans.pdf
07-Clustering-II.ipynb
07-Clustering-II.pdf
08A-Clustering-III-Hierarchical.pdf
08B-Clustering-III.ipynb
08B-Clustering-III.pdf
09-Clustering-IV-GMM-EM.ipynb
09-Clustering-IV-GMM-EM.pdf
10-Low-Rank-and-SVD.ipynb
10-Low-Rank-and-SVD.pdf
11-Dimensionality-Reduction-SVD-II.ipynb
11-Dimensionality-Reduction-SVD-II.pdf
12-Anomaly-Detection-SVD-III.ipynb
12-Anomaly-Detection-SVD-III.pdf
13-Web-Scraping.pdf
14-Classification-Decision-Trees.pdf
15A-Classification-II-kNN.pdf
15B-Classification-II-Demo.ipynb
15B-Classification-II-Demo.pdf
16A-Classification-III-NB-SVM.pdf
16B-Classification-III-Random-Projection.ipynb
16C-Classification-III-SVM-Demo.ipynb
16C-Classification-III-SVM-Demo.pdf
17-Regression-I-Linear.ipynb
17-Regression-I-Linear.pdf
18-Regression-II-Logistic.ipynb
18-Regression-II-Logistic.pdf
19-Regression-III-More-Linear.ipynb
19-Regression-III-More-Linear.pdf
20-Recommender-Systems-Edited.pdf
20-Recommender-Systems.pdf
21A-MapReduce.pdf
21B-MapReduce-Demo.ipynb
22A-Networks-I-Intro-Edited.pdf
22A-Networks-I-Intro.pdf
22B-Networks-I-Intro-Demo.ipynb
22B-Networks-I-Intro-Demo.pdf
23-Networks-II-Centrality.ipynb
23-Networks-II-Centrality.pdf
24-Networks-III-Clustering.ipynb
24-Networks-III-Clustering.pdf
25-Networks-MapReduce.pdf
CS505FinalProject-Fall2016.pdf
Makefile
README.md
laUtilities.py
postamble.tex
preamble.tex
slideUtilities.py
stripHiddenCode.py
stripheaders.py
syllabus.pdf
syllabus.tex

README.md

CS506-Computational-Tools-for-Data-Science

Repository for CS 505 / ENG 500 as taught by Mark Crovella - BU Computer Science

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