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CoCalc: Collaborative Calculation in the Cloud

Standards-conformant acoustics library for Python: measurement and metrology, building, environmental and room acoustics, psychoacoustics, electroacoustics, vibration, underwater and aircraft/rotorcraft noise. Every method is implemented from the standard and validated against reference data, with teaching-style docs (formerly PyOctaveBand).

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.