| Apache Mahout - Mahout
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| Dask - a flexible parallel computing library for analytic computing.
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| dask-ml - parallel and distributed machine learning using Dask alongside existing machine learning libraries like Scikit-Learn: 1) accelerating existing algorithms within Scikit-Learn 2) Implementing new parallel algorithms 3) Deploying other distributed services like XGBoost or TensorFlow.
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| Dlib - a modern C toolkit containing machine learning algorithms and tools for creating complex software in C .
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| FACTORIE - is a toolkit for deployable probabilistic modeling, implemented as a software library in Scala. It provides its users with a succinct language for creating relational factor graphs, estimating parameters and performing inference.
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| KeyStone - a software framework, written in Scala, from the UC Berkeley AMPLab designed to simplify the construction of large scale, end-to-end, machine learning pipelines with Apache Spark.
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| Kubeflow - an open, community driven project to make it easy to deploy and manage an ML stack on Kubernetes.
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| LEARNSC - SVM, NN and FL MATLAB based user-friendly routines.
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| MeTA a modern C++ data science toolkit |
| Microsoft DMTK - Distributed Machine Learning Tookit
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| MLlib - Apache Spark's scalable machine learning library.
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| mlpack - is an intuitive, fast, scalable C++ machine learning library, meant to be a machine learning analog to LAPACK. It aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers.
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| Netlab - Matlab toolbox including Gaussian Process Regression, Mixture models and Neural Networks.
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| OpenCV (Open Source Computer Vision) - is a library of programming functions for real time computer vision. It includes a statistical learning software for several methods, including naive Bayes, SVM, and gradient boosting.
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| PaddlePaddle - (PArallel Distributed Deep LEarning) is an easy-to-use, efficient, flexible and scalable deep learning platform, which is originally developed by Baidu scientists and engineers for the purpose of applying deep learning to many products at Baidu.
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| Photon-ML - A scalable machine learning library on Apache Spark (by LinkedIn)
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| QuickNet - QuickNet is a suite of software that facilitates the use of multi-layer perceptrons (MLPs) in statistical pattern recognition systems. It is primarily designed for use in speech processing but may be useful in other areas.
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| Ray system for parallel and distributed Python that unifies the ML ecosystem. |
| ScalaNLP - a suite of machine learning and numerical computing libraries.
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| scikit-learn - machine learning in Python.
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| statnet - a suite of software packages for network analysis that implement recent advances in the statistical modeling of networks.
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| Suite of Fast Incremental Algorithms for Machine Learning. |
| TADM The Toolkit for Advanced Discriminative Modeling |
| The Kernel-Machine Library: Software and Tutorials for ML |
| TMVA Toolkit for Multivariate Data Analysis with ROOT - Supports several ML algorithms including SVM, (boosted) decision trees, and neural networks.
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| torch - is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and provides a very efficient implementation, thanks to an easy and fast scripting language, LuaJIT, and an underlying C implementation.
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| TorchCraft - an interface between StarCraft: Brood War and Torch, the deep learning environment.
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| TorchGPipe - A GPipe implementation in PyTorch
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| Turi Create - Apple's framework to simplify development of custom ML models.
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| Vowpal Wabbit - Fast machine learning
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| WEKA - Weka (Waikato Environment for Knowledge Analysis) is a popular package of machine learning and data mining software written in Java, developed at the University of Waikato. WEKA is free software available under the GNU General Public License.
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