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Quality Over Quantity in Data Training
The key to effectively training machine learning algorithms is having quality data and individuals who can validate the data. In medical imaging, for instance, it is crucial to have radiologists confirm the findings to ensure accurate training. Simply having vast amounts of data is insufficient if the data is noisy or incorrect. Quality data is emphasized over quantity to prevent teaching algorithms inaccurate information.