CS506-Computational-Tools-for-Data-Science

(β˜… 96)

Repository for CS 506 / ENG 500 as taught by Mark Crovella - BU Computer Science

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  • 01-Intro-to-Python.ipynb
  • 02A-Git-Jupyter.ipynb
  • 02B-Pandas.ipynb
  • 03-Probability-and-Statistics-Refresher.ipynb
  • 04-Linear-Algebra-Refresher.ipynb
  • 05-Distances-Timeseries.ipynb
  • 06-Clustering-I-kmeans.ipynb
  • 07-Clustering-II-in-practice.ipynb
  • 08-Clustering-III-hierarchical.ipynb
  • 09-Clustering-IV-GMM-EM.ipynb
  • 10-Low-Rank-and-SVD.ipynb
  • 11-Dimensionality-Reduction-SVD-II.ipynb
  • 12-Anomaly-Detection-SVD-III.ipynb
  • 13-Learning-From-Data.ipynb
  • 14-Classification-I-Decision-Trees.ipynb
  • 15-Classification-II-kNN.ipynb
  • 16-Classification-III-NB-SVM.ipynb
  • 17-Regression-I-Linear.ipynb
  • 18-Regression-II-Logistic.ipynb
  • 19-Regression-III-More-Linear.ipynb
  • 20-Recommender-Systems.ipynb
  • 21-Networks-I.ipynb
  • 22-Networks-II-Centrality-Clustering.ipynb
  • 23-Gradient-Descent.ipynb
  • _config.yml
  • _toc.yml
  • als.py
  • amazon-recs-dense-submatrix.csv.gz
  • common.py
  • Dockerfile
  • landing-page.md
  • laUtilities.py
  • lmafit.py
  • ln_preamble.py
  • Makefile
  • MF.py
  • README.md
  • requirements.in
  • requirements.txt
  • slideUtilities.py

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