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Adding metrics and plots to dvc.yaml

In this exercise, your task is to complete the contents of dvc.yaml that defines a model training workflow.

Here preprocess_dataset.py and train.py are the files that perform data preprocessing and model training by taking weather.csv as input in the raw_dataset folder. As output, the model training code generates a predictions.csv file that contains the predictions and the ground truth, and metrics.json file containing structured metrics data. The former would be used to generate a normalized confusion matrix plot for comparing it with previous commits.

This exercise is part of the course

CI/CD for Machine Learning

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