Jithsaavvy/Deploying-an-end-to-end-keyword-spotting-model-into-cloud-server-by-integrating-CI-CD-pipeline
The project is a concoction of research (audio signal processing, keyword spotting, ASR), development (audio data processing, deep neural network training, evaluation) and deployment (building model artifacts, web app development, docker, cloud PaaS) by integrating CI/CD pipelines with automated tests and releases.
This project helps MLOps engineers deploy end-to-end keyword spotting models into a cloud server. It automates the entire machine learning lifecycle, from training the model with audio files to packaging it as a web application and deploying it with CI/CD. The primary user is an MLOps engineer or a machine learning practitioner responsible for taking models from development to production.
No commits in the last 6 months.
Use this if you are an MLOps engineer looking for a comprehensive pipeline to train, track, and deploy keyword spotting models as a web application on a cloud server with integrated CI/CD.
Not ideal if you are a data scientist or researcher primarily focused on model development and evaluation without the need for automated deployment pipelines.
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Last pushed
Sep 04, 2022
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