Answer Posted / Jaldhari Meena

The three stages of building a hypothesis or model in machine learning are: (1) Data Preparation - cleaning, preprocessing, and selecting relevant features. (2) Model Training - using an algorithm to learn patterns from the data and build a model that can make predictions on new data. (3) Model Evaluation - assessing the performance of the model using appropriate evaluation metrics and making necessary adjustments.

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