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Extra Resources

  • Courses
    • Brown Intro to ML (Felzenszwalb)
    • Brown Intro to ML (Sudderth)
    • Dartmouth Intro to ML (Lorenzo Torresani)
    • Brown Intro to Computer Vision (Hays)
    • Bryn Mawr ML (Eaton)
    • Oregon State CS 434: ML and Data Mining (Xiaoli Fern)
    • Swarthmore AI (Meeden)
    • UPenn CIS 419/519 Intro to ML (Eaton)
    • UPenn CIS 520 ML (Ungar)
    • Stanford CS 229 (Ng)
  • MATLAB
    • Brown Intro to ML MATLAB tutorial
    • Brown Intro to Computer Vision MATLAB tutorial
    • yagtom: Yet Another Guide MATLAB
    • Coursera Octave tutorial
  • Data Sets
    • UCR Time Series Data
    • TODO: UCI
    • MNIST
    • Kaggle
  • Papers
    • Salzberg S. On comparing classifiers: Pitfalls to avoid and a recommended approach. Data Mining and Knowledge Discovery 1997; 1:317–327
    • Ratanamahatana, C. A. and Keogh. E, Everything you know about Dynamic Time Warping is Wrong
    • Mitchell chapter on decision trees
    • A Neural Network for Factoid Question Answering over Paragraphs by Mohit Iyyer, Jordan Boyd-Graber, Leonardo Claudino, Richard Socher, Hal Dauḿe III, EMNLP 2014.