Jupyter magics and kernels for working with remote Spark clusters
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General-purpose, formally-verified, 64-bit operating system in SPARK/Ada for x86-64
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.
- svm
- regression
- classification
- machine-learning
HiRTOS: a high-integrity multi-core RTOS kernel and separation kernel written in SPARK Ada
An attempt at a minimalistic and secure operating system.