4.2: Gathering, refining, and using data effectively for ML model datasets

Опубликовано 6 февраля 2023, 16:07

Learn the essential concepts around gathering good quality training data that is clean (free of mistakes or errors) and unbiased to ensure the best results possible from the resulting custom model you wish to make. You will also learn the importance of splitting your data into training, validation, and testing datasets to avoid overfitting and ensuring the best ML model creation with the data you have.

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