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DMTK
DMTK

3
11
+ 1
0
Leaf
Leaf

13
24
+ 1
0
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DMTK vs Leaf: What are the differences?

Developers describe DMTK as "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. On the other hand, Leaf is detailed as "Machine learning framework in Rust". Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack.

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

DMTK and Leaf are both open source tools. It seems that Leaf with 5.4K GitHub stars and 270 forks on GitHub has more adoption than DMTK with 2.69K GitHub stars and 595 GitHub forks.

What is DMTK?

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 Leaf?

Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack.
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            What are some alternatives to DMTK and Leaf?
            TensorFlow
            TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
            scikit-learn
            scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
            Keras
            Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
            PyTorch
            PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
            ML Kit
            ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
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