Software Alternatives, Accelerators & Startups

MLOps VS Datatron

Compare MLOps VS Datatron and see what are their differences

MLOps logo MLOps

MLOps is a software platform that enables companies to manage AI production.

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
  • MLOps Landing page
    Landing page //
    2023-10-05
  • Datatron Landing page
    Landing page //
    2023-02-11

MLOps videos

MLOps explained | Machine Learning Essentials

More videos:

  • Review - Coursera Machine Learning Engineering for Production (MLOps) Specialization Review
  • Review - What is MLOps?

Datatron videos

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 MLOps and Datatron)
Business & Commerce
100 100%
0% 0
Data Science And Machine Learning
Data Dashboard
100 100%
0% 0
Data Science Notebooks
0 0%
100% 100

User comments

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What are some alternatives?

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

SAS Model Manager - SAS Model Manager is a proven, reliable solution for the Analysis Services platform that enables you to integrate multiple environments, tools, and applications using open REST APIs.

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.

Digital.ai - Digital.ai is an intelligent value stream management software platform for digital enterprises and application delivery teams.

MCenter - Machine Learning Operationalization

Xyonix - Xyonix is an AI Consulting and Data Science Solution that brings AI, Machine Learning, and Deep Learning to businesses by providing Software Engineering and Advisory services.

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.