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Datatron VS Managed MLflow

Compare Datatron VS Managed MLflow and see what are their differences

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Datatron logo Datatron

Datatron automates the deployment, monitoring, governance, and validation of your machine learning models in scikit-learn, TensorFlow, Keras, Pytorch, R, H20 and SAS

Managed MLflow logo Managed MLflow

Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
  • Datatron Landing page
    Landing page //
    2023-02-11
  • Managed MLflow Landing page
    Landing page //
    2023-05-15

Datatron videos

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Harish Doddi demos Datatron @SFNewTech on 1 Mar 2017 #SFNT @getdatatron

More videos:

  • Review - Virtual Records Management from Datatron

Managed MLflow videos

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Category Popularity

0-100% (relative to Datatron and Managed MLflow)

Datatron

Managed MLflow

Data Science And Machine Learning
35 35%
Data Science And Machine Learning
65% 65
Machine Learning Tools
53 53%
Machine Learning Tools
47% 47
Data Science Notebooks
42 42%
Data Science Notebooks
58% 58
Data Dashboard
100 100%
Data Dashboard
0% 0

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What are some alternatives?

When comparing Datatron and Managed MLflow, you can also consider the following products

Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

MCenter - Machine Learning Operationalization

neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

Weights & Biases - Developer tools for deep learning research

Numericcal - Machine Learning Operationalization

Iterative.ai - Iterative removes friction from managing datasets and ML models and introduces seamless data scientists collaboration.

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