Shogun Machine Learning Toolbox
Unified and efficient Machine Learning
The Shogun Machine learning toolbox provides a wide range of unified and efficient Machine Learning (ML) methods. The toolbox seamlessly allows to easily combine multiple data representations, algorithm classes, and general purpose tools. This enables both rapid prototyping of data pipelines and extensibility in terms of new algorithms. We combine modern software architecture in C++ with both efficient low-level computing backends and cutting edge algorithm implementations to solve large-scale Machine Learning problems (yet) on single machines.
We have various ideas for this years Summer of Code. This year, our focus is not on adding new ML algorithms, but on rather software engineering driven goals, in particular
- framework re-factoring & clean-ups
- efficiency & benchmarks
Please read how to get involved with us before applying. Then please use the scheme shown below for your student application. If you have any questions, ask on the mailing list (firstname.lastname@example.org, please note that you have to be subscribed in order to post) or IRC #shogun on freenode.
Shogun Machine Learning Toolbox 2017 Projects
Data Project - Patient Monitoring and Decision Support using Health DataFor GSoC2017, I intend to use the Shogun library on health data and show the usefulness of machine learning in applications that could save people's...
Fundamental Machine Learning AlgorithmsShogun implements dozens of machine learning and related algorithms, however many of them are not properly benchmarked and the library suffer from a...
Shogun Detox II: Codebase improvements and finalization of the new Tags and Serialization frameworks.The Shogun Toolbox is a well-established machine learning project that provides efficient algorithms implementations that can be used in a wide range...
The Shogun Detox2Every line of code in SHOGUN has a long history and have gone through many brains and hands. This made SHOGUN what it is today: a powerful toolbox...