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ML Visualization IDE vs DMTK: What are the differences?

Developers describe ML Visualization IDE as "Make powerful, interactive machine learning visualizations". Debug your machine learning models in realtime with powerful, interactive visualizations Quickly log charts from your Python script, visualize your model development in live dashboards, and share interactive plots with your team, in just 2 minutes.. On the other hand, DMTK is detailed 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.

ML Visualization IDE and DMTK can be primarily classified as "Machine Learning" tools.

Some of the features offered by ML Visualization IDE are:

  • Powerful, interactive visualizations
  • Quickly log charts
  • Visualize your model development in live dashboards

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.

DMTK is an open source tool with 2.77K GitHub stars and 597 GitHub forks. Here's a link to DMTK's open source repository on GitHub.

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- No public GitHub repository available -

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 ML Visualization IDE?

Debug your machine learning models in realtime with powerful, interactive visualizations. Quickly log charts from your Python script, visualize your model development in live dashboards, and share interactive plots with your team, in just 2 minutes.

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    What are some alternatives to DMTK and ML Visualization IDE?
    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.
    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.
    Keras
    Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
    scikit-learn
    scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
    CUDA
    A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
    See all alternatives