How do I choose the right model for my machine learning project?

How do I choose the right model for my machine learning project?

Choosing the right model depends on various factors like the type of data, the problem you're solving, and performance metrics. What kind of data are you working with?

I have a dataset with both numerical and categorical features.

For mixed data types, you might consider models like Random Forest or Gradient Boosting. Have you thought about the specific problem type, like classification or regression?

I'm working on a classification problem.

Great! For classification, you could also explore logistic regression or support vector machines. Do you have a preferred evaluation metric?

I'm looking at accuracy and F1 score.

Both are excellent metrics! You might want to try cross-validation to ensure your model generalizes well. Would you like tips on that?