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Homeworks Homework6 Apr 26, 2017
data datasets Apr 13, 2017
01-Intro-to-Python.ipynb HW0 Jan 25, 2017
01-Intro-to-Python.pdf lecture 1 Jan 20, 2017
02-Pandas.ipynb
02A-Getting-Started.ipynb HWs Jan 30, 2017
02A-Getting-Started.pdf HWs Jan 30, 2017
03-Probability-and-Statistics-Refresher.ipynb lecture 3 Jan 31, 2017
03-Probability-and-Statistics-Refresher.pdf
04-Linear-Algebra-Refresher.ipynb
05-Distances-Timeseries.ipynb Homework-2-2 Mar 16, 2017
06A-Clustering-Overview.ipynb Homework-2-2 Mar 16, 2017
06B-Kmeans.pdf
07-Clustering-II.ipynb Lecture 7 Feb 16, 2017
08-Hierarchical-Density.ipynb
08A-Hierarchical.pdf lecture 8 Feb 23, 2017
08B-density-clustering.pdf
09-Clustering-IV-GMM-EM.ipynb lecture 9 Feb 28, 2017
10-Low-Rank-and-SVD.ipynb lecture 10 Mar 2, 2017
11-Dimensionality-Reduction-SVD-II.ipynb lecture 11 Mar 16, 2017
12-Anomaly-Detection-SVD-III.ipynb
14-Classification-Decision-Trees.pdf
15A-Classification-II-kNN.pdf
15B-Classification-II-Demo.ipynb
16A-Classification-III-NB-SVM.pdf lect 16 Apr 4, 2017
16B-Classification-III-SVM-Demo.ipynb
17-Regression-Linear.ipynb
18-Regression-II-Logistic.ipynb logistic Apr 13, 2017
19-Networks-I-Intro.pdf lecture 19 Apr 18, 2017
20-Networks-II-Centrality.ipynb
21-Networks-III-Clustering.ipynb
22-RecommendationSystems.pdf lect 22 Apr 27, 2017
README.md Readme Jan 19, 2017
Webscraping.pdf WebScraping Mar 31, 2017
apple_jobs_scraper.py WebScraping Mar 31, 2017
laUtilities.py utilities Feb 7, 2017
slideUtilities.py utilities Feb 7, 2017
syllabus.pdf syllabus Jan 19, 2017
syllabus.tex syllabus Jan 19, 2017
youtube_scraper.py

README.md