PAC Learning
Probably Approximately Correct framework - sample complexity, consistent learners, finite hypothesis classes, and the formal foundation of why data size matters in ML.
Probably Approximately Correct framework - sample complexity, consistent learners, finite hypothesis classes, and the formal foundation of why data size matters in ML.