With so many machine learning models to choose from, how do you decide which one is best for a specific problem? Do you usually go for simpler models first, like linear regression, or do you start with something more complex like a random forest? I’d love to hear about your approach to model selection and whether there are specific factors (like dataset size or complexity) that guide your decision-making process.