If you have a trained machine or deep learning model and want to deploy it on our platform, check out the Model Deployment Guides where you'll see tutorials for popular frameworks such as Scikit-learn (including a hands-on video), PyTorch, and Tensorflow.
Learn how to create and publish your algorithmsGet Started Now
If you have a trained machine or deep learning model and want to deploy it on our platform, check out the Deploy Model Guides where you'll see tutorials for popular frameworks such as Scikit-learn, PyTorch, and Tensorflow.
Best Practices and Deep Dives for Algorithm Development and Model Deployment
Follow these tips to create the best algorithm profile possible.
How to handle errors between algorithms.
Create, Update, Publish, and Delete Algorithms via the Algorithmia API
Using CI/CD to (re)deploy your ML models via Jenkins or GitHub Actions
This guide will walk you through the steps to implement your own evaluation.
Reloading your ML Model when it changes
Controlling where the source code for your algorithm resides
Getting your algorithm on Algorithmia is easy. Find out how with this tutorial.
Markdown syntax for Algorithm descriptions.