This legacy version of AI Platform Prediction is deprecated and will no longer be available on Google Cloud after January 31, 2025. All models, associated metadata, and deployments will be deleted after January 31, 2025. Migrate your resources to Vertex AI to get new machine learning features that are unavailable in AI Platform.
Using scikit-learn on Kaggle and AI Platform Prediction
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You can deploy scikit-learn models trained in Kaggle to AI Platform Prediction for
serving predictions at scale.
This AI Adventures episode explains the basic workflow about how to take a model
trained anywhere, including Kaggle, and serve online predictions from
AI Platform Prediction.
Save your model using the
sklearn.externals.joblib library,
making sure to name the file model.joblib. Select the Commit & Run
button to execute all of your kernel code cells in order. This saves and runs
your model training code.
You can download your model files from the Output tab in your kernel.
At the main link to your kernel,
https://www.kaggle.com/[YOUR-USER-NAME]/[YOUR-KERNEL-NAME]/:
Select the Output tab at the top of the page.
Your model.joblib file appears in a list of Data Sources. To
download the file, select the Download All button. Alternatively, hover
your mouse over the name of the model, and then select the download icon
that appears by the model name.