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Energy-based machine learning models built upon PyTorch.
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A pure Go implementation of the prediction part of GBRTs, including XGBoost and LightGBM.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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A generic approach that allows to mimic most factorization models by feature engineering.
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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.
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LightlySSL is a Python computer vision framework for self-supervised learning on images, written in a PyTorch-like style. It exposes low-level building blocks such as loss functions and model heads, supports custom backbone models for self-supervised pre-training, and supports distributed training using PyTorch Lightning. Sample code covers models including MoCo, SimCLR, BYOL and DINO.
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Explaining the predictions of any machine learning classifier.
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A comprehensive toolkit to build Machine Learning applications with Rust.
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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.
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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.
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An interactive educational game built for the Google Gemma 3n Impact Challenge. It uses Gemma 3n via Ollama for on-device, structured educational conversations about sustainable farming and botany, and runs locally with no internet required for core features.
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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.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Machine Learning library for the web, Node.js and developers.
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A model-agnostic visual debugging tool for machine learning.
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ManifoldLearning.jl is a Julia package for manifold learning and nonlinear dimensionality reduction. It provides methods including Isomap, diffusion maps, locally linear embedding, Hessian eigenmaps, Laplacian eigenmaps, local tangent space alignment and t-SNE. Most methods use k-nearest neighbors to construct local subspace representation, and a custom k-nearest neighbors function is suggested for large datasets.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Application-oriented deep reinforcement learning framework addressing real-world decision problems.
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MCGrad is a tool for multicalibration that aims to keep machine learning model predictions calibrated globally and across segments defined by features. It requires Python 3.10+ and is installed with pip or conda; the project's own description says it has been deployed at Meta on hundreds of production models.
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MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto-differentiation.