Answer / Saket Vishnoi

The three stages to build the hypotheses or model in machine learning are: 1. Data Collection, where data is gathered and preprocessed; 2. Model Training, where a hypothesis is learned based on the training set of examples; 3. Model Testing, where the learned hypothesis is evaluated against the test set of examples.

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