Track, compare and collaborate on Machine Learning experiments
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What is allows data science teams and individuals to automagically track their datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility. is a tool in the Machine Learning Tools category of a tech stack.

Who uses

3 companies reportedly use in their tech stacks, including New Yorker, SupplyPike, and Machine Learning.

9 developers on StackShare have stated that they use Integrations

TensorFlow, PyTorch, scikit-learn, Keras, and Theano are some of the popular tools that integrate with Here's a list of all 7 tools that integrate with
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Best tool for comparing experiments Alternatives & Comparisons

What are some alternatives to
MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
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 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 is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano.
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48 developers follow to keep up with related blogs and decisions.