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Comet.ml

12
48
+ 1
3
TransmogrifAI

8
20
+ 1
0
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Comet.ml vs TransmogrifAI: What are the differences?

What is Comet.ml? Track, compare and collaborate on Machine Learning experiments. Comet.ml allows data science teams and individuals to automagically track their datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility.

What is TransmogrifAI? Automated machine learning for structured data (by Salesforce). TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Spark with minimal hand tuning.

Comet.ml and TransmogrifAI belong to "Machine Learning Tools" category of the tech stack.

TransmogrifAI is an open source tool with 1.57K GitHub stars and 271 GitHub forks. Here's a link to TransmogrifAI's open source repository on GitHub.

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Pros of Comet.ml
Pros of TransmogrifAI
  • 3
    Best tool for comparing experiments
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    - No public GitHub repository available -

    What is Comet.ml?

    Comet.ml allows data science teams and individuals to automagically track their datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility.

    What is TransmogrifAI?

    TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Spark with minimal hand tuning

    Need advice about which tool to choose?Ask the StackShare community!

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    What tools integrate with Comet.ml?
    What tools integrate with TransmogrifAI?

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    What are some alternatives to Comet.ml and TransmogrifAI?
    MLflow
    MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
    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.
    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/
    See all alternatives