gyrdym/ml_algo

Provides native implementations of supervised learning (logistic/linear regression, decision trees, KNN) and unsupervised algorithms (KDTree, locality-sensitive hashing) with multiple optimization backends (SGD, batch gradient descent, Newton-Raphson). Integrates with the ml_ecosystem stack—ml_preprocessing for feature engineering, ml_dataframe for tabular data manipulation, and ml_linalg for linear algebra—enabling end-to-end ML workflows on Dart VM, Flutter, and WebAssembly targets.

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