What are automated tuning techniques in machine learning?

What are automated tuning techniques in machine learning?

Automated tuning techniques are methods used to optimize machine learning models by automatically adjusting hyperparameters.

Can you give me some examples of these techniques?

Sure! Examples include Grid Search, Random Search, and Bayesian Optimization.

How do these techniques compare in terms of efficiency?

Grid Search is exhaustive but slow, Random Search is faster but less thorough, while Bayesian Optimization is efficient and adaptive.

Which technique would you recommend for a beginner?

I recommend starting with Random Search as it's easier to implement and understand for beginners.