Train an Iris classifier in Google Cloud Workbench and save the trained model to Cloud Storage. Follow the process from project setup to checking the uploaded model file.
In this walkthrough:
• Configure Workbench and open JupyterLab
• Upload your notebook and datasets
• Resolve permission, import, and file-path issues
• Train and evaluate a decision tree classifier
• Save the model with Joblib and upload it to Cloud Storage
CHAPTERS
00:00 What we’re building
00:25 Project and services
00:54 Workbench configuration
01:34 Notebook and data
02:03 Storage permissions
02:43 Environment and dataset path
03:27 Train and evaluate
04:00 Save and upload the model
04:33 Recap
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