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
- 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.Go Top