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Introduction to Python for Data Science

The notebooks here will run through examples using popular PyData libraries.

For Mac users: my install steps for Python 3.5 and useful libraries.

Topics covered:

  • Pandas to read csv and linear regression with scikit-learn
  • Image analysis to count circles with openCV
  • Text analysis by web scraping with BeautifulSoup and construct a count matrix with scikit-learn
  • Time series analysis using FFT and curve-fitting from numpy and filtering time series with statsmodel.