• Machine Learning and Performance Evaluation — Overcoming the Selection Bias. Predictive modeling has become such a crucial part of our everyday life. It’s such an important topic. I am really looking forward to giving you an intro at DataPhilly on November 30th! [Slides] [Video]
  • Invited talk on our novel approach to protein-ligand docking mode prediction based on graph theory @ BMB Departmental Retreat at Michigan State (Oct 14 2016) [Slides] [Video]
  • Again, I had such a great time at yet another Python & Data Science conference. Here are the tutorial materials from my PyData Chicago 2016 talk: “Learning scikit-learn – An Introduction to Machine Learning in Python”
    @ PyData Chicago 2016 [GitHub Repo] [Slides] [Video]
  • Presentation of a novel approach to protein-ligand binding mode prediction by rigidity analysis using graph theory
    @ BioMolecular Sciences Gateway [Slides]

  • SeaScreen - A large-scale, hypothesis-driven virtual screening framework for structure-based inhibitor discovery
    @ GLB in Toronto

  • An Introduction to Supervised Machine Learning and Pattern Classification: The Big Picture
    @ NextGen Bioinformatics [Slides]

  • MusicMood - Machine Learning in Automatic Music Mood Prediction Based on Song Lyrics
    @ PSA Group [Slides]

  • […]



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