What are the three stages of building the hypotheses or model in machine learning?
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The three stages of building a machine learning model are:
Model Building
Choose a suitable algorithm for the model and train it according to the requirement
The six steps to building a machine learning model include:
Model Testing
In machine learning, model testing is referred to as the process where the performance of a fully trained model is evaluated on a testing set. The testing set consisting of a set of testing samples should be separated from the both training and validation sets, but it should follow the same probability distribution as the training set.
Applying the Model
Make the required changes after testing and use the final model for real-time projects