3 Google summer of code for scikit-learn and more…

under machine learning programming scipy scikit-learn   Read time: 1 min. Tweet

The scikit-learn got 3 students accepted for the Google summer of code.

• Imanuel Bayer will work on making our sparse linear models, for regression and classification, faster. His proposal Optimizing sparse linear models using coordinate descent and strong rules.
• David Marek will implement multi-layer perceptrons for the scikit. His proposal: Multilayer Perceptron
• Vlad Niculae will work on speeding up the library in general, catching all the low hanging fruits, and the ones a bit higher. His proposal: Need for scikit-learn speed

In addition, other related projects have exciting projects, for instance **statsmodels**:

• Divyanshu Bandil: Extension of Linear to Non Linear Models in Statsmodels Python module
• Alexandre Crayssac: estimating system of equations
• Justin Grana: empirical Likelihood in Statsmodels
• Georgi Panterov: nonparametric estimation

and Cython:

• Philip Herron: pxd generation using gcc-python-plugin
• Mark Florisson: Fast Numerical Computing with Cython

finally, in Pandas:

• Vytautas Jancauskas: Plots in pandas

Congratulations to all of the students. This is going to be an exciting summer.

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