Node.js wrapper of scikit-learn
Scikit-Learn for JS
A scikit-learn-inspired machine learning library for Bun/TypeScript.
scikit-learn is a module for machine learning
node wrapper for python's scikit-learn
n8n nodes for scikit-learn machine learning algorithms
Transform features by scaling each feature to a given range. References from scikit-learn
High-performance TypeScript clustering algorithms (K-Means, Spectral, Agglomerative) with TensorFlow.js acceleration and scikit-learn compatibility
Comprehensive Machine Learning plugin with 10 specialist agents: TensorFlow/Keras, PyTorch, RL, Scikit-learn, Neural Architecture, Gradient Boosting, Computer Vision, NLP Transformers, Time Series, and AutoML. Context7-verified patterns.
Run scikit-learn models in TypeScript. Zero dependencies.
This package provides utilities for training and deploying machine learning models on AWS SageMaker. It supports multiple ML frameworks including PyTorch, TensorFlow, XGBoost, Scikit-learn, and HuggingFace.
HDBSCAN clustering in Rust/WASM — ported from scikit-learn, optimized for 2D Euclidean distance
Machine Learning Scikit-Learn
Use Python's #1 machine learning library from Node.js
Hdbscan implementation in JavaScript
Machine Learning Scikit-Learn
t-SNE implementation in JavaScript
Text classify with Machine learning for node-red.
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A framework for building native apps using React
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Babel plugin for React Compiler.
i18next internationalization framework
A set of utils for faster development of GraphQL tools
Python bindings for sklears machine learning library using PyO3
Feature selection algorithms for sklears - scikit-learn compatible ML in Rust
A scikit-learn inspired machine learning library in Rust
A scikit-learn equivalent for Rust — re-export crate
Gaussian Process models for regression and classification
A comprehensive machine learning library in Rust, inspired by scikit-learn
Naive Bayes classifiers for sklears - scikit-learn compatible ML in Rust
State-of-the-art clustering algorithms for Rust - surpassing scikit-learn, HDBSCAN, and RAPIDS cuML
A RobustScaler for Rust, compatible with scikit-learn's RobustScaler
High-performance SIMD acceleration primitives for the Sklears machine learning ecosystem
State-of-the-art clustering algorithms for Rust - surpassing scikit-learn, HDBSCAN, and RAPIDS cuML
Fundamental operations for scientific computing directly with Polars
scikit-learn wrapper for Ruby
SVMKit is a machine learninig library in Ruby. SVMKit provides machine learning algorithms with interfaces similar to Scikit-Learn in Python. SVMKit supports Linear / Kernel Support Vector Machine, Logistic Regression, Linear Regression, Ridge, Lasso, Factorization Machine, Naive Bayes, Decision Tree, AdaBoost, Random Forest, K-nearest neighbor algorithm, K-Means, DBSCAN, Principal Component Analysis, and Non-negative Matrix Factorization. Note that the SVMKit has been deprecated and has been renamed to Rumale.
Rumale is a machine learning library in Ruby. Rumale provides machine learning algorithms with interfaces similar to Scikit-Learn in Python. Rumale supports Support Vector Machine, Logistic Regression, Ridge, Lasso, Multi-layer Perceptron, Naive Bayes, Decision Tree, Gradient Tree Boosting, Random Forest, K-Means, Gaussian Mixture Model, DBSCAN, Spectral Clustering, Mutidimensional Scaling, t-SNE, Fisher Discriminant Analysis, Neighbourhood Component Analysis, Principal Component Analysis, Non-negative Matrix Factorization, and many other algorithms.
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