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Comet.ml

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ml5.js

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Comet.ml vs ml5.js: 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 ml5.js? Friendly machine learning for the web. ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.

Comet.ml and ml5.js can be categorized as "Machine Learning" tools.

ml5.js is an open source tool with 2.72K GitHub stars and 213 GitHub forks. Here's a link to ml5.js's open source repository on GitHub.

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Pros of Comet.ml
Pros of ml5.js
  • 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 ml5.js?

    ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.

    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 ml5.js?
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        What are some alternatives to Comet.ml and ml5.js?
        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