Modelbit

Deploy ML models.

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Console’s review

· Reviewed by David Mytton

What we like

Build & deploy models from Jupyter notebooks. Provides an inference endpoint accessible via a REST JSON API and from within data warehouses e.g. from SQL, Redshift, or Snowflake. Supports custom environments, packages, tests. Can also run training jobs from a notebook or from Git. Includes logs, monitoring & version control.

Tradeoffs

Everything is based around Python & Notebooks - this is the standard ML stack, but worth being aware of if you’re using something else.

Is Modelbit a fit?

Based on Console’s review published on 2023-05-18. Summary updated .

Who it’s for

Machine learning developers using Python and Jupyter notebooks should consider this tool

Why consider it

It allows deploying ML models with a REST JSON API and custom environments

Keep in mind

It may not be suitable for developers using non-Python environments

Console is a free weekly newsletter with short reviews of developer tools, covering strengths and tradeoffs. This review reflects Console’s assessment at publication on 2023-05-18. Features and limitations may have changed since the review date. Read our selection criteria and learn about Console.

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