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Moa: MOA is an open source framework for Big Data stream mining. It is listed under Data & Analytics on AI Registry as a free tool.
The tools below are approved listings in the same category, ordered by how closely their tags match Moa. This is an automatic list. We have not written a researched verdict for Moa yet, so treat it as a shortlist and check each vendor's pricing page before switching.
Built from each tool's listing. Vendors can update their own listing after claiming it.
Tribuo - A Java machine learning library
Tribuo is an open source machine learning library written in Java and maintained by Oracle. It gives Java developers a single, strongly typed interface for classification, regression, clustering, anomaly detection and multi label classification, along with tools for model development and evaluation. The library wraps ...
An open-source toolkit for large-scale genomic analysis
Glow is an open source toolkit for large scale genomic analysis, built natively on Apache Spark. It lets researchers aggregate genomic data and run data preparation, statistical analysis and machine learning at biobank scale and beyond, using the same Spark SQL engine that many organizations already use for petabyte cl...
AI powered open source recommender system engine supports classical/LLM rankers and multimodal content via embedding
Gorse is an open source recommender system engine written in Go. You import items, users and interaction data, and the system automatically trains models to generate recommendations for each user. It aims to be a universal recommender that can be added to a wide range of online services, such as content sites, shops an...
LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence https://arxiv.org/abs/2609.17488
LimiX is a family of foundation models for structured data, meaning rows and columns of tabular data. The current release, LimiX 2, is built around a design the developers call Contextual Mechanism Networks. Instead of training a separate model for each dataset, a single pretrained model reads a table as context and ca...
Machine Learning in R
The mlr package is a machine learning framework for the R programming language. It provides a single interface to a large number of classification, regression, survival analysis and clustering methods, so users do not need to write separate wrappers for each algorithm in R. Around that interface it supplies the surrou...
nannyml: post-deployment data science in python
NannyML is a post deployment monitoring product for machine learning models. Its core idea is to estimate model performance when ground truth labels are delayed or missing, so a team can see how a model is doing and be alerted when performance drops rather than when data merely drifts. The company says this cuts false ...