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Continual VS Managed MLflow

Compare Continual VS Managed MLflow and see what are their differences

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Contents:
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  2. » Reviews
  3. » Alternatives

Continual logo Continual

Continual is the easiest way to build continually improving predictive models - from customer churn to inventory forecasts - directly on your cloud data warehouse.

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.
  • Continual Landing page
    Landing page //
    2023-08-24
  • Managed MLflow Landing page
    Landing page //
    2023-05-15

Category Popularity

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

Continual

Managed MLflow

AI
100 100%
AI
0% 0
Data Science And Machine Learning
16 16%
Data Science And Machine Learning
84% 84
Developer Tools
100 100%
Developer Tools
0% 0
Data Science Notebooks
0 0%
Data Science Notebooks
100% 100

User comments

Share your experience with using Continual and Managed MLflow. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Continual seems to be more popular. It has been mentiond 1 time since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Continual mentions (1)

  • Thoughts on SQL based auto-ML style tools
    Does anyone here use tools such as continual or postgresml? Basically ml on sql tools. Source: about 2 years ago

Managed MLflow mentions (0)

We have not tracked any mentions of Managed MLflow yet. Tracking of Managed MLflow recommendations started around Mar 2021.

What are some alternatives?

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

Lobe - Visual tool for building custom deep learning models

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.

anon - Machine learning, automated

Weights & Biases - Developer tools for deep learning research

Evidently AI - Open-source monitoring for machine learning 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.

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