A comprehensive, modular collection of fundamental Machine Learning algorithms implemented from scratch in pure Python and NumPy — without relying on high-level ML libraries like Scikit-Learn for the ...
Distributed AI training coordinates data, parameters, activations, gradients, and optimizer state across many accelerators so ...
Self-supervised learning creates training targets from the structure of unlabeled data, allowing models to learn ...
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), ...
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