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Comet.ml

11
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3
ScalaNLP

2
12
+ 1
0
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Comet.ml vs ScalaNLP: What are the differences?

Developers describe Comet.ml as "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. On the other hand, ScalaNLP is detailed as "A suite of machine learning and numerical computing libraries". ScalaNLP is a suite of machine learning and numerical computing libraries.

Comet.ml and ScalaNLP can be primarily classified as "Machine Learning" tools.

ScalaNLP is an open source tool with 2.91K GitHub stars and 674 GitHub forks. Here's a link to ScalaNLP's open source repository on GitHub.

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Pros of Comet.ml
Pros of ScalaNLP
  • 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 ScalaNLP?

    ScalaNLP is a suite of machine learning and numerical computing libraries.

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

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    What companies use ScalaNLP?
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      What tools integrate with Comet.ml?
      What tools integrate with ScalaNLP?

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      What are some alternatives to Comet.ml and ScalaNLP?
      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