What are the differences between Automated ML and Traditional ML?

What are the differences between Automated ML and Traditional ML?

Automated ML (AutoML) simplifies the machine learning process by automating tasks like feature selection and model tuning, while Traditional ML requires manual intervention for these tasks.

Can you give me examples of when to use each?

Use Automated ML for quick prototyping or when you lack deep ML expertise. Traditional ML is better for complex problems requiring custom solutions.

What tools are available for Automated ML?

Popular tools for Automated ML include Google Cloud AutoML, H2O.ai, and Microsoft Azure Machine Learning.

Is Automated ML less accurate than Traditional ML?

Not necessarily. AutoML can achieve comparable accuracy, but it may depend on the specific use case and data quality.