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ML for QA automation
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Module 9
Deployment: Shipping Your Tool
1
Building CLI Tools with Typer/Click
Build a Command-Line Interface (CLI) for local usage of your tool using a library like Typer or Click.
2
Deploying ML Models with FastAPI
Expose your ML pipeline as a REST API using a web framework like FastAPI.
Dockerizing Your Application
Containerize your application and its dependencies using Docker for reproducibility.
Crafting a Stellar README.md
Write a comprehensive README.md detailing the project’s purpose, setup, and usage examples.
5
Publishing to GitHub: Project & Licensing
Publish the final project to a public GitHub repository with a descriptive summary and an open-source license.
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