MLflow vs Postman
Overview
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CLI (Node.js)
Manual
Detailed Comparison
It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide. | MLflow is an open source platform for managing the end-to-end machine learning lifecycle. |
Compact layout;HTTP requests with file upload support;Formatted API responses for JSON and XML;Image previews;Request history;Basic Auth, OAuth 1.0, OAuth 2.0, and other common auth helpers;Autocomplete for URL and header values;Key/value editors for adding parameters or header values. Works for URL parameters too.;Use environment variables to easily shift between settings. Great for testing production, staging or local setups.;Keyboard shortcuts to maximize your productivity;Automatically generated web documentation;Mock servers hosted on Postman’s cloud;API monitoring run from Postman cloud | Track experiments to record and compare parameters and results; Package ML code in a reusable, reproducible form in order to share with other data scientists or transfer to production; Manage and deploy models from a variety of ML libraries to a variety of model serving and inference platforms |
Statistics | |
GitHub Stars - | GitHub Stars 22.8K |
GitHub Forks 0 | GitHub Forks 5.0K |
Stacks 96.1K | Stacks 228 |
Followers 82.5K | Followers 524 |
Votes 1.8K | Votes 9 |
Pros & Cons | |
Pros
Cons
| Pros
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Integrations | |
| No integrations available | |
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