What are the best practices for determining dataset sizes?

What are the best practices for determining dataset sizes?

When determining dataset sizes, consider factors like the complexity of the task, model architecture, and available data.

How do I know if my dataset is large enough?

You can assess if your dataset is large enough by evaluating model performance, overfitting, and validation metrics.

Are there any specific guidelines for different types of models?

Yes, different models have varying data requirements. For instance, deep learning models typically need larger datasets than traditional ML models.

What if I don't have enough data?

If you lack sufficient data, consider data augmentation, transfer learning, or using synthetic data to enhance your dataset.