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MLOps Engineer Deploys Heart-Sound Classifier for Patient Data

An MLOps engineer details the process of deploying a heart-sound classifier, moving beyond the notebook environment to a real-world application. The project involved training and validating the model on approximately 1,800 patients. This case study highlights the practical challenges and steps involved in taking a machine learning model from development to production. AI

IMPACT Demonstrates the practical application of machine learning in healthcare, moving models from development to real-world patient data analysis.

RANK_REASON The item describes the deployment of a specific ML model for a practical application, which falls under the 'tool' category as it's about applying existing technology.

Read on Medium — MLOps tag →

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MLOps Engineer Deploys Heart-Sound Classifier for Patient Data

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  1. Medium — MLOps tag TIER_1 English(EN) · Omarhatemmoahemd ·

    When Your Model Leaves the Notebook: Deploying a Heart-Sound Classifier on ~1,800 Patients

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@omarhatemmoahemd/when-your-model-leaves-the-notebook-deploying-a-heart-sound-classifier-on-1-800-patients-198b8db28aa6?source=rss------mlops-5"><img src="https://cdn-images-1.medium.com/max/16…