Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Lightly is a computer vision framework for self-supervised learning.
Explaining the predictions of any machine learning classifier.
A comprehensive toolkit to build Machine Learning applications with Rust.
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.
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.
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.
Class on machine w/ PDF, lectures, code.
Machine Learning library for the web, Node.js and developers.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
A model-agnostic visual debugging tool for machine learning.
A Julia package for manifold learning and nonlinear dimensionality reduction.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Application-oriented deep reinforcement learning framework addressing real-world decision problems.
A production-ready library for multicalibration, fairness, and bias correction in machine learning models.