DBoost stochastic gradient boosting via Ridge with random dummies
Stochastic Dummy Boosting. Contribute to mikeskim/dboost development by creating an account on GitHub.
DBoost stochastic gradient boosting via Ridge with random dummies launched on March 4, 2016 with 8 votes, #2,148 of 4,409 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 10 years on.
Does a similar job
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Boldly go where Gradient Descent has never gone before with DiscoGrad2024 · github.com · ▲232Trying to do gradient descent using automatic differentiation over branchy programs? Or to combine them with neural networks for end-to-end training? Then this might be interesting to you. We develped DiscoGrad, a tool for automatic differentiation through C++ programs involving input-dependent control flow (e.g., "if (f(x) < c) { ... }", differentiating wrt. x) and randomness. Our initial motivation was to enable the use of gradient descent with simulations, which often rely heavily on such discrete branching. The latter makes plain autodiff mostly useless, since it can only account for the…
SVG Mesh Gradient Generator2022 · magicpattern.design · ▲257Create unique customizable SVG gradients with MagicPattern
Fullstack ML – From Notebooks to Deployment2019 · github.com · ▲198Contribute to xadrianzetx/fullstack.ai development by creating an account on GitHub.
Provide a CSV and a target field, generate a model and code to run it2019 · github.com · ▲172Provide an input CSV and a target field to predict, generate a model + code to run it. - minimaxir/automl-gs
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Launched alongside, March 2016
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Franz▲877Franz combines WhatsApp, Slack, Telegram, Gmail, Outlook, and native Signal in one desktop app with AI summaries, workspaces, and privacy-conscious local features.
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