What are the best practices for training data in AI?

What are the best practices for training data in AI?

The best practices for training data include ensuring data quality, diversity, and relevance, as well as proper labeling.

How do I ensure the quality of my training data?

To ensure quality, you should clean the data, remove duplicates, and validate it against reliable sources.

What is the importance of data diversity?

Data diversity helps the model generalize better and reduces bias, making it more effective across different scenarios.

Can you explain the role of data labeling?

Data labeling is crucial as it provides the necessary context for the model to learn from the training data.