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.

⭐️⭐️⭐️ Don't forget to subscribe to be notified of future videos ⭐️⭐️⭐️
⭐️⭐️⭐️ Want to buy me a coffee? I can always use more :) https://www.buymeacoffee.com/julsimon ⭐️⭐️⭐️

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

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

For more content, follow me on :
* Medium: https://medium.com/@julsimon
* Twitter: https://twitter.com/juliensimon

Видео Deploying Machine Learning Models with mlflow and Amazon SageMaker канала Julien Simon