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Numericcal VS Datatron

Compare Numericcal VS Datatron and see what are their differences

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Numericcal logo Numericcal

Machine Learning Operationalization

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
  • Numericcal Landing page
    Landing page //
    2023-05-15
  • Datatron Landing page
    Landing page //
    2023-02-11

Numericcal videos

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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

Category Popularity

0-100% (relative to Numericcal and Datatron)

Numericcal

Datatron

Data Science And Machine Learning
48 48%
Data Science And Machine Learning
52% 52
Data Science Notebooks
48 48%
Data Science Notebooks
52% 52
Machine Learning Tools
46 46%
Machine Learning Tools
54% 54
Machine Learning
100 100%
Machine Learning
0% 0

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What are some alternatives?

When comparing Numericcal and Datatron, 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

5Analytics - The 5Analytics AI platform enables you to use artificial intelligence to automate important commercial decisions and implement digital business models.

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.

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.

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

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