AI and ML Fundamentals CLOUD-DIGITAL-LEADER Practice Questions (Page 4)

Questions 16–20

1. 16expert · hard

   A manufacturing company wants to use ML to predict equipment failures. They have years of sensor data, but some sensors have been malfunctioning, leading to gaps and outliers. They also have a team of engineers who can label which failures actually occurred. What is the most important step to ensure the ML model is reliable?

   • ARely on the engineers' labels to correct any data issues.
   • BUse a deep learning model that can automatically handle noisy data.
   • CCollect more data from the malfunctioning sensors to fill the gaps.
   • DClean the sensor data by handling missing values and outliers before training.
   Reveal Solution Discussion Select an answer first
2. 17application · medium

   A logistics company wants to predict the expected delivery time for each shipment based on factors like distance, weather, and traffic. They have historical data with actual delivery times. Which type of machine learning problem does this represent?

   • AClassification
   • BData analytics
   • CRegression
   • DClustering
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4. 18application · medium

   A healthcare provider wants to use ML to analyze unstructured clinical notes to identify patients at risk of readmission. What is a key business value of using ML for this task?

   • AIt guarantees that all patients at risk will be identified.
   • BIt can process large volumes of unstructured text that would be impractical to analyze manually.
   • CIt replaces the need for human doctors in decision-making.
   • DIt eliminates the need for data cleaning because ML can handle any data.
   Reveal Solution Discussion Select an answer first
5. 19expert · hard

   A telecom company wants to reduce customer churn. They have historical data on customer usage, complaints, and demographics. They also have a team of data analysts who currently produce monthly churn reports. The company wants to identify customers likely to churn in the next 30 days so they can offer targeted retention offers. What is the most effective approach?

   • AUse the analysts' reports to manually identify at-risk customers each month.
   • BImplement a clustering model to group customers by behavior and target the largest cluster.
   • CTrain a classification model on historical churn data to predict which customers will churn.
   • DUse a regression model to predict the exact date of churn for each customer.
   Reveal Solution Discussion Select an answer first
6. 20application · medium

   A city is using ML to predict traffic congestion. The training data is collected from sensors that are sometimes faulty, leading to missing or incorrect readings. What is the most likely impact on the model?

   • AThe model will be less accurate and may make unreliable predictions.
   • BThe model will require more computational resources to process the faulty data.
   • CThe model will automatically correct the faulty readings.
   • DThe model will become more robust due to the noisy data.
   Reveal Solution Discussion Select an answer first