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scikit-learn
Analyzed about 5 hours ago
scikit-learn is a Python module integrating various machine learning algorithms under a common interface. It offers a wide range of methods such as Support Vector Machines, linear models (L1, L2 penalized), logistic regression, gaussian mixture models and more. The large number of algorithms aleady
Licenses:
BSD-3-Clause
Accord.NET Framework
Analyzed about 18 hours ago
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications. A comprehensive set
Licenses:
lgpl21_or...
SHOGUN
Analyzed about 5 hours ago
The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic interface for SVMs, features several SVM and kernel implementations, includes LinAdd optimizations and also Multiple Kernel Learning algorithms.
Licenses:
gpl3_or_l...
ai4r
Analyzed about 7 hours ago
AI4R is a collection of ruby algorithm implementations, covering several Artificial intelligence fields, and simple practical examples using them. A Ruby playground for AI researchers.
Licenses:
mozilla_p...
zeta-learn
Analyzed about 19 hours ago
zeta-learn is a minimalistic python machine learning library designed to deliver fast and easy model prototyping.
zeta-learn aims to provide an extensive understanding of machine learning through the use of straightforward algorithms and readily implemented examples making it a useful resource for researchers and students.