Bender vs DMTK: What are the differences?
Bender: A Deep Learning framework for iOS. Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood; 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.
Bender and DMTK can be primarily classified as "Machine Learning" tools.
Some of the features offered by Bender are:
- Neural networks
- deep learning
On the other hand, DMTK provides the following key features:
- 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.
Bender and DMTK are both open source tools. DMTK with 2.69K GitHub stars and 595 forks on GitHub appears to be more popular than Bender with 1.65K GitHub stars and 87 GitHub forks.