What are the main challenges in machine learning?

What are the main challenges in machine learning?

Some key challenges include data quality, overfitting, algorithm selection, and interpretability.

Can you explain data quality issues?

Data quality issues can arise from missing values, noise, and bias in the data, affecting model performance.

What is overfitting and how can it be avoided?

Overfitting occurs when a model learns noise instead of the signal. It can be avoided using techniques like cross-validation and regularization.

Why is interpretability important in machine learning?

Interpretability is crucial for trust and accountability, especially in critical applications like healthcare and finance.