Machine Learning & Data Mining

• Classifying Complex Networks (scikit-learn, networkX)

  
  • The code to extract the publicly available databases and to calculate the topological features for the graph databases is here.
  • The code to cleanse and organize the data is here.
  • The code to perform the machine learning for many (supervised and unsupervised) methods is here.
  • A talk about the project is here. The first draft of the paper is here.

• Grad Class in Machine Learning (Python)

  • Material from the graduate course at Stony Brook University. The source code for the homework is here, with many algorithms in Python/NumPy comparing Naive-Bayes vs. Logistic Regression, performing Adaboost, and comparing kNN vs. SVM.
  • My theoretical homework, from the entire course, is here.

• Information Diffusion in Twitter

  A very introductory essay about graphs and information diffusion in social network, under supervision of Prof. K. Mueller. Simple examples of high-dimensional space parameterizing each tweet to capture the information diffusion and graph layout.

• Data Analysis in Astronomy (IDL)

  Data extraction, calibration, and cleansing for astrophysical images for photometry and spectroscopy:
  • On the Spectroscopy Study of the Earthshine Spectra: report and source code.
  • On the Calculation of the Angular Diameter of the Sun by Michelson Radio Interferometer: report and source code.
  • On the Measurement of Stellar Fluxes on the Interstellar Dust Extinction of M35: report and source code.