What are the limitations of automated machine learning in Python?

What are the limitations of automated machine learning in Python?

Automated machine learning (AutoML) in Python can simplify model selection and hyperparameter tuning, but it has limitations.

Can you elaborate on those limitations?

Sure! Some limitations include lack of interpretability, potential overfitting, and dependency on quality data.

How does lack of interpretability affect model deployment?

Lack of interpretability can hinder trust and acceptance from stakeholders, making it difficult to justify model decisions.

Are there specific scenarios where AutoML is not recommended?

Yes, AutoML may not be ideal for highly specialized domains or when domain expertise is crucial for feature engineering.