An Introduction To Shogun Machine Learning Toolbox One For All
summary
Shogun is a C++ machine‑learning toolbox born in 1999 with 300,000 lines of code on GitHub that provides a unified interface to swap SVM implementations and kernel choices and easily compare solvers. It exposes algorithms to Python, C#, Java and others via SWIG‑based bindings, uses templates and shared pointers for model construction and training, and reports successful multi‑language examples and ongoing C++17 migration efforts.
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chapters (5)
- 0:00Start
- 0:11SHOGUN MACHINE LEARNING TOOLBOX
- 0:53EXAMPLE: LINEAR SUPPORT VECTOR MACHINE (SVM)
- 1:37EXAMPLE: SUPPORT VECTOR MACHINE
- 2:21INTERFACES STANDARD TO CUTTING EDGE ML LIBRARIES
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