How can I overcome challenges in machine learning?

What are some common challenges in machine learning?

Common challenges include data quality, model selection, overfitting, and interpretability.

How can I improve the quality of my training data?

You can improve data quality by cleaning the data, removing duplicates, and ensuring it's representative of the problem.

What strategies can I use to avoid overfitting?

To avoid overfitting, you can use techniques like cross-validation, regularization, and simplifying your model.

Can you explain model interpretability and why it's important?

Model interpretability helps stakeholders understand how decisions are made, which is crucial for trust and compliance.