Your team is working on an NLP model and has just operationalized the first model. Your team makes updates to the model, overwrites the original model, and puts this new model into operation. However, one of the teams using the model has seen a decrease in performance and is asking to use the original model.
What critical error did your team make?

• A.They did not have a model retraining pipeline that took into account models
• B.They did not practice model iteration and properly iterate on the model
• C.They did not practice model versioning and keep all versions of the model
• D.They did not have data governance in place

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You are leading a project to develop a new predictive maintenance solution. Together with your project team you determine your data needs, see if you have access to the data, and then begin working on the project. Which phase best describes the work you are performing?

• A.Phase V
• B.Phase VI
• C.Phase IV
• D.Phase II
• E.Phase III
• F.Phase I

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A project manager is reviewing the performance of an AI model used for predictive analytics in sales. The model's accuracy is within acceptable limits; however, its precision is low.
What is the cause for the precision issue?

• A.The feature selection process is flawed
• B.The model is underfitting the validation data
• C.The model is overfitting the training data
• D.The training data is unbalanced

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Your team has created a model that is going to be used for monitoring systems and it needs to provide analysis on a weekly basis. What's the most appropriate Model Operationalization approach?

• A.Stream learning
• B.Real-time prediction
• C.Web service / Microservice
• D.Batch prediction

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A retail bank wants to reduce fraudulent transactions by detecting unusual card activity in near real time. Which AI capability should be used?

• A.Predictive analytics
• B.Conversational
• C.Hyperpersonalization
• D.Autonomous systems

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