Audience

Data scientists searching for a complete Machine Learning solution

About Modelbit

Don't change your day-to-day, works with Jupyter Notebooks and any other Python environment. Simply call modelbi.deploy to deploy your model, and let Modelbit carry it — and all its dependencies — to production. ML models deployed with Modelbit can be called directly from your warehouse as easily as calling a SQL function. They can also be called as a REST endpoint directly from your product. Modelbit is backed by your git repo. GitHub, GitLab, or home grown. Code review. CI/CD pipelines. PRs and merge requests. Bring your whole git workflow to your Python ML models. Modelbit integrates seamlessly with Hex, DeepNote, Noteable and more. Take your model straight from your favorite cloud notebook into production. Sick of VPC configurations and IAM roles? Seamlessly redeploy your SageMaker models to Modelbit. Immediately reap the benefits of Modelbit's platform with the models you've already built.

Integrations

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Company Information

Modelbit
Founded: 2022
United States
www.modelbit.com

Videos and Screen Captures

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Product Details

Platforms Supported
Cloud
Training
Documentation
Live Online
Support
Online

Modelbit Frequently Asked Questions

Q: What kinds of users and organization types does Modelbit work with?
Q: What languages does Modelbit support in their product?
Q: What kind of support options does Modelbit offer?
Q: What other applications or services does Modelbit integrate with?
Q: What type of training does Modelbit provide?

Modelbit Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Templates
Visualization
Statistical / Mathematical Tools