PLearn is a large C++ machine-learning library with a set of Python tools and Python bindings. It is mostly a research platform for developing novel algorithms, and is being used extensively at Yoshua Bengio and Pascal Vincent's University of Montreal lab. PLearn was designed from the beginning (1999) for high performance and to handle large datasets that may not fit in memory.
- Changes to previous version:
Initial Announcement on mloss.org.
- BibTeX Entry: Download
- URL: Project Homepage
- Supported Operating Systems: Cygwin, Linux, Macosx
- Data Formats: None
- Tags: Regression, Classifiaction, Deep Belief Networks, Deep Learning, Density Estimation, Dimensionality Reduction, Gradient Based Learning, Large Scale Learning, Manifold Learning, Neural Networks, Nonpar
- Archive: download here
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