Deploying Machine Learning Models with mlflow and Amazon SageMaker скачать в хорошем качестве

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/sagema... Documentation: https://www.mlflow.org/ For more content, follow me on : Medium:   / julsimon   Twitter:   / juliensimon