AI use cases and applicationsFull notesSummaryRingkasanStoriesPracticeMachine Learning5 exam-style questions on this lesson.Question 1 of 5A company needs to calculate sales tax on each order using a fixed rate set by law. Should it use machine learning?AYes, because ML is always more accurate than fixed rulesBYes, because the number of orders each day is largeCNo, because ML models cannot handle numeric inputsDNo, because the answer comes from a known, simple calculationCheck answerQuestion 2 of 5Why is spam filtering a good fit for machine learning?AIt depends on many overlapping signals that are hard to write as rulesBSpam messages never change, so a fixed model works foreverCML can filter spam without needing any example emailsDSpam can be defined by one simple keyword ruleCheck answerQuestion 3 of 5A team must review millions of transactions a day for suspicious patterns. Which reason for using ML does this show?AThe data is unlabeledBThe scale is too big for peopleCThe answer must be exact and deterministicDThe rules are simple and knownCheck answerQuestion 4 of 5How do ML models differ from traditional programs?AML models do not need testing once they are trainedBML models never make mistakes on data they have not seenCML models learn patterns from data and can improve with more dataDML models follow hard-coded rules written by developersCheck answerQuestion 5 of 5. Select two.Which TWO situations are NOT a good fit for machine learning? (Select TWO.)ADetecting fraudulent card payments across millions of transactionsBApplying a fixed 10% discount to orders over $100CConverting temperatures from Celsius to FahrenheitDPredicting customer churn from behavior dataERecognizing objects in photosCheck answer0 of 2 selectedExamples of AI Applications6 exam-style questions on this lesson.Machine Learning Techniques and Use Cases10 exam-style questions on this lesson.