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Python library for automatic extraction of relevant features from time series.
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XGBoost is a scalable, portable and distributed gradient boosting library. It supports multiple programming languages including Python, R, Java, Scala and C, and can run on single machines or distributed frameworks such as Hadoop, Spark, Dask, Flink and DataFlow.
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Repository of Ultralytics YOLO models, including YOLO27, YOLO26, YOLO11, and YOLOv8, covering object detection, instance segmentation, semantic segmentation, image classification, pose estimation, and object tracking. Models can be installed as the ultralytics package, used through a CLI yolo command or Python, and exported to formats such as ONNX.
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Zetane Viewer is a free tool for visualizing machine learning and artificial neural network models, including architecture and internal data such as feature maps, weights, biases and layer output tensors. The viewer supports .ONNX and .ZTN files and is available for Windows, Linux and Mac. It can also be launched from existing scripts or notebooks via the Zetane Python API.