Making The Most Out of This Book – Your Certification and BeyondComparing AI, ML, and DLExamining MLExamining DLClassifying supervised, unsupervised, and reinforcement learningIntroducing supervised learningThe CRISP-DM modeling life cycleData splittingOverfitting and underfittingApplying cross-validation and measuring overfittingBootstrapping methodsThe variance versus bias trade-offShuffling your training setModeling expectationsIntroducing ML frameworksML in the cloudSummaryExam Readiness Drill – Chapter Review QuestionsExam Readiness DrillATTEMPT 1ATTEMPT 2ATTEMPT 3Working On Timing