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Related Questions
- What is data curation and how can it help ensure representative training data?
- How can data sampling techniques, such as stratified sampling, be used to achieve representative training data?
- What are some common biases that can affect training data and how can they be mitigated?
- How can data augmentation techniques, such as image rotation and flipping, be used to increase the diversity of training data?
- What is the role of domain knowledge in ensuring that training data is representative of the population it is intended to model?
- How can active learning techniques be used to select the most informative data points for the model, ensuring that the training data is representative?
- What are some best practices for collecting and annotating data to ensure that it is representative of the population it is intended to model?
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