Version control for machine learning with support to Amazon S3 and Google Cloud Storage.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Run Keras models in the browser, with GPU support provided by WebGL 2.
Kernel density estimators for Julia.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Machine Learning Toolkit for Kubernetes.
Machine Learning Pipelines for Kubeflow.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.
Simple, concise implementations of machine learning techniques and utilities in Clojure.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Energy-based machine learning models built upon PyTorch.
A pure Go implementation of the prediction part of GBRTs, including XGBoost and LightGBM.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
A generic approach that allows to mimic most factorization models by feature engineering.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Lightly is a computer vision framework for self-supervised learning.