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Hypertunity is a lightweight, high-level Python library for black-box hyperparameter optimisation. It supports Bayesian optimisation by wrapping GPyOpt, objective function evaluation through a scheduler that is also compatible with Slurm, and real-time visualisation of results in Tensorboard via the HParams plugin. A Trial wrapper class allows parallel optimisation without manual scheduling, optimiser updates and logging.
Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, specialized for real-time large scale machine learning. It is a framework for building applications and includes packaged end-to-end applications for collaborative filtering, classification, regression and clustering. The repository was archived by the owner on May 3, 2022, and is read-only.
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection. The repository includes training, validation, inference, and multi-format export tooling, and reuses shared utilities from the ultralytics package. Detection is framed as a single regression problem predicting bounding boxes and class probabilities from full images in one forward pass.
