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11,041–11,064 of 15,396 · Most stars

Signals is a framework for developing enterprise and SaaS applications that follows the USE-CASE driven methodology

Long-term, cross-project memory for AI coding agents. Your own Obsidian vault as the source of truth. Daemonless and without opaque databases, your memory belongs to you.

Spring data gremlin makes it easier to implement Graph based repositories. This module extends Spring Data to allow support for potentially any Graph database that implements the Tinkerpop Blueprints 2.x API.

Elixir implementation of the Git object storage, but with the goal to implement the same semantic with other storage and topics

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.