BU-CS506-Spring2018

BU CS506 (Computational Tools for Data Science) as taught by Adam Smith

Name		Name	Last commit message	Last commit date
Latest commit History 41 Commits
data		data
figs		figs
01-Intro-to-Python.ipynb		01-Intro-to-Python.ipynb
01-Intro-to-Python.pdf		01-Intro-to-Python.pdf
02A-Getting-Started.ipynb		02A-Getting-Started.ipynb
02A-Getting-Started.pdf		02A-Getting-Started.pdf
02B-Pandas.ipynb		02B-Pandas.ipynb
02B-Pandas.pdf		02B-Pandas.pdf
03-Distances-Timeseries.ipynb		03-Distances-Timeseries.ipynb
04-Linear-Algebra-Refresher.ipynb		04-Linear-Algebra-Refresher.ipynb
05-Probability-and-Statistics-Refresher.ipynb		05-Probability-and-Statistics-Refresher.ipynb
06A-Clustering-Overview.ipynb		06A-Clustering-Overview.ipynb
06B-Kmeans-slides.pdf		06B-Kmeans-slides.pdf
06C-k-means-examples.ipynb		06C-k-means-examples.ipynb
07-Clustering-II.ipynb		07-Clustering-II.ipynb
07B-Clustering-III.ipynb		07B-Clustering-III.ipynb
08-Clustering-IV-GMM-EM.ipynb		08-Clustering-IV-GMM-EM.ipynb
09-Low-Rank-and-SVD.ipynb		09-Low-Rank-and-SVD.ipynb
10-Dimensionality-Reduction-SVD-II.ipynb		10-Dimensionality-Reduction-SVD-II.ipynb
10A-Anomaly-Detection-SVD-III.ipynb		10A-Anomaly-Detection-SVD-III.ipynb
11-Classification-Decision-Trees.pdf		11-Classification-Decision-Trees.pdf
12-Classification-II-kNN.pdf		12-Classification-II-kNN.pdf
12B-Classification-II-Demo.ipynb		12B-Classification-II-Demo.ipynb
13-Webscraping-slides.pdf		13-Webscraping-slides.pdf
13-Webscraping.ipynb		13-Webscraping.ipynb
14-Classification-III-NB-SVM-slides.pdf		14-Classification-III-NB-SVM-slides.pdf
14A-Classification-III-SVM-Demo.ipynb		14A-Classification-III-SVM-Demo.ipynb
15-Regression-introduction.ipynb		15-Regression-introduction.ipynb
15B-Regression-I-Linear.ipynb		15B-Regression-I-Linear.ipynb
16-Regression-II-Logistic.ipynb		16-Regression-II-Logistic.ipynb
16B-Regression-III-More-Linear-not-covered-in-class.ipynb		16B-Regression-III-More-Linear-not-covered-in-class.ipynb
17-Neural-Networks-Intro.pptx		17-Neural-Networks-Intro.pptx
17B-DNN-classifier-tensorflow.ipynb		17B-DNN-classifier-tensorflow.ipynb
18-19-Interpretation-I-and-II.pdf		18-19-Interpretation-I-and-II.pdf
18-19-Interpretation-I-and-II.pptx		18-19-Interpretation-I-and-II.pptx
18-Interpretation-I.pdf		18-Interpretation-I.pdf
20-Ethics.pptx		20-Ethics.pptx
22-Recommender-Systems-Edited.pdf		22-Recommender-Systems-Edited.pdf
23-Networks-I-Intro.pdf		23-Networks-I-Intro.pdf
23B-Networks-I-Intro-Demo.ipynb		23B-Networks-I-Intro-Demo.ipynb
24-Networks-II-Clustering.ipynb		24-Networks-II-Clustering.ipynb
CS506-2018-Spring-course-intro.pptx		CS506-2018-Spring-course-intro.pptx
LICENSE		LICENSE
README.md		README.md
iris_data.py		iris_data.py
laUtilities.py		laUtilities.py
slideUtilities.py		slideUtilities.py
stripHiddenCode.py		stripHiddenCode.py
stripheaders.py		stripheaders.py
syllabus.pdf		syllabus.pdf
syllabus.tex		syllabus.tex

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