NovaML.jl

⚠️ IMPORTANT NOTE: NovaML.jl is currently in alpha stage. It is under active development and may contain bugs or incomplete features. Users should exercise caution and avoid using NovaML.jl in production environments at this time. We appreciate your interest and welcome feedback and contributions to help improve the package.

NovaML.jl aims to provide a comprehensive and user-friendly machine learning framework written in Julia. Its objective is providing a unified API for various machine learning tasks, including supervised learning, unsupervised learning, and preprocessing, feature engineering etc.

Main objective of NovaML.jl is to increase the usage of Julia in daily data science and machine learning activities among students and practitioners.

Currently, the module and function naming in NovaML is similar to that of Scikit Learn to provide a familiarity to data science and machine learning practitioners. However, NovaML is not a wrapper of ScikitLearn.

Features

• Unified API using Julia's multiple dispatch and functor-style callable objects
• Algorithms for classification, regression, and clustering
• Preprocessing tools for data scaling, encoding, and imputation
• Model selection and evaluation utilities
• Ensemble methods