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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.

:star: A confidence-based rating system with scope and cache enabled

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graphql-gradle-plugin is a Gradle Plugin for GraphQL, based on graphql-java. It accelerates the development for both the client and the server, by generating the Java code. It allows a quicker development when in contract-first approach, by avoiding to code the boilerplate code.

:chart_with_upwards_trend: A live cryptocurrency historical trade data blotter. Download live historical trade data from any cryptoexchange, be it for machine learning, backtesting/visualizing trading strategies or for Quantopian/Zipline.