SHARK Alternatives [Page 2]

DataScience combines human intellect with machine-powered analysis to create actionable insights from complex data.

Attivio Machine Learning analyzes user behaviors and builds relevancy models that learn and improve as content, data, and user activity grows and evolves.

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Build and deploy machine learning models in a simplified way with Azure Machine Learning service. Make machine learning more accessible with automated capabilities.

Google Cloud Machine Learning is a service that enables user to easily build machine learning models, that work on any type of data, of any size.

Open Source

Optimize Everything. Tune your experiments automatically to get better results, faster. A/B testing.

pyBrain is a modular machine learning library for python that offer a flexible and powerful algorithms for machine learning task and a variety of predefined environments to test and compare algorithms.

DatumBox is a machine learning framework that can be applied to a wide variety of complex applications, though it's primarily used for social media analytics.

Open Source

MLlib is Spark's machine learning (ML) library that make practical machine learning scalable & provides ML Algorithms.

DecisionTree.jl is a Julia classifier with the implimentation of the ID3 algorithm with post pruning, parallelized bagging, adaptive boosting, cross validation and support for mixed nominal and numerical data.

Pylearn2 is a library for machine learning research.

Open Source

HLearn is a high performance machine learning library written in Haskell.

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.

Open Source

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Open Source