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Julien Simon for AWS

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Deploying Machine Learning Models with mlflow and Amazon SageMaker

In this video, I first train an XGBoost model on my local machine (I use PyCharm), and visualize results in the mlflow UI. Then, I deploy the model locally, and predict test data. Next, I create a Docker container, push it to Amazon ECR, and use it to deploy my model on Amazon SageMaker.

Happy to answer any question you may have!

Code: https://gitlab.com/juliensimon/sagemaker-automation/-/tree/master/mlflow/direct-marketing-xgboost

Documentation: https://www.mlflow.org/

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Oldest comments (1)

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swati2901

Hi Julien,

I have tried mlflow on windows10 but ui is not opening.

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Join Developer Advocate Luce Carter for a hands-on tutorial on building an AI-powered dinner recommendation agent. Discover how to integrate Microsoft Semantic Kernel, MongoDB Atlas, C#, and OpenAI for ingredient checks and smart restaurant suggestions.

Watch the video 📺

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