Posted Wednesday at 05:39 AM2 days I'm working on a prediction project with a limited dataset (~5,000 rows). Should I use deep learning or stick with classic ML models like Random Forest or SVM? What are the risks and trade-offs, and how do I decide?
I'm working on a prediction project with a limited dataset (~5,000 rows). Should I use deep learning or stick with classic ML models like Random Forest or SVM? What are the risks and trade-offs, and how do I decide?