Machine Learning

Machine Learning at UofT

The Department of Computer Science at the University of Toronto has several faculty members working in the area of machine learning, neural networks, statistical pattern recognition, probabilistic planning, and adaptive systems. In addition, many faculty members inside and outside the department whose primary research interests are in other areas have specific research projects involving machine learning in some way.

  • Deep Learning Discovers Genetic Causes of Diseases

    Wired Magazine describes how Toronto researchers used deep learning to make new discoveries about the genetics of disease. Also check out the Science article describing this work. Image by Olena Shmahalo/Quanta Magazine.

  • Toronto Deep Learning Projects

    Check out the exciting deep learning research in our group and the new website for deep learning projects!

  • pqR – a pretty quick version of R

    pqR is a new version of the R interpreter. It is based on R-2.15.0, distributed by the R Core Team, but improves on it in many ways, mostly ways that speed it up, but also by implementing some new features and fixing some bugs.

  • SHRiMP

    SHRiMP is a software package for aligning genomic reads against a target genome. It was primarily developed with the multitudinous short reads of next generation sequencing machines in mind, as well as Applied Biosystem’s colourspace genomic representation.


  • Deep Learning Discovers Genetic Causes of Diseases

    Jan 6th, 15
    [Read More]
  • Chris Maddison won the Outstanding Paper Award at NIPS 2014

    Dec 15th, 14
    [Read More]
  • 6 papers accepted by NIPS 2014

    Dec 1st, 14
    [Read More]