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Iterative Improvement ๐ŸŒŸ

Finding a good set of weights isnโ€™t the endโ€”itโ€™s just the beginning.

Machine learning's real power comes from its ability to keep adjusting and improving these weights. This process is called iterative improvement, where we continuously refine and adjust our weights to make better predictions.

This method of using random weights and then adjusting them based on actual outcomes is a foundational concept in machine learning. It allows the Machine Learning Model to โ€˜learnโ€™ from data and improve over time.