DMTK vs PredictionIO

DMTK vs PredictionIO: What are the differences?

What is DMTK? Microsoft Distributed Machine Learning Tookit. DMTK provides a parameter server based framework for training machine learning models on big data with numbers of machines. It is currently a standard C++ library and provides a series of friendly programming interfaces.

What is PredictionIO? Open Source Machine Learning Server. PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.

DMTK and PredictionIO belong to "Machine Learning Tools" category of the tech stack.

Some of the features offered by DMTK are:

• DMTK Framework: a flexible framework that supports unified interface for data parallelization, hybrid data structure for big model storage, model scheduling for big model training, and automatic pipelining for high training efficiency.
• LightLDA, an extremely fast and scalable topic model algorithm, with a O(1) Gibbs sampler and an efficient distributed implementation.
• Distributed (Multisense) Word Embedding, a distributed version of (multi-sense) word embedding algorithm.

On the other hand, PredictionIO provides the following key features:

• Integrated with state-of-the-art machine learning algorithms. Fine-tune, evaluate and implement them scientifically.
• Customize the modularized open codebase to fulfill any unique prediction requirement.
• Built on top of scalable frameworks such as Hadoop and Cascading. Ready to handle data of any scale.

DMTK and PredictionIO are both open source tools. It seems that PredictionIO with 11.8K GitHub stars and 1.92K forks on GitHub has more adoption than DMTK with 2.69K GitHub stars and 595 GitHub forks.