Allianz Financial Services (AFS) is a banking group offering end-to-end banking and financial solutions in South East Asia through its consumer banking, business banking, Islamic banking, investment finance and stock broking businesses as well as unit trust and asset administration, having served the financial community over the past five decades.
AFS being one the largest banks in the region is planning to improve its segment business by launching a campaign to identify potential customers for various new products launched based on their past behavior? AFS is looking for both batch and real-time predictive analytics
AFS understands that they are losing customers to competitive banks and a campaign is launched to address customer retention. AFS has identified a long list of potential customers that have reduced transactions with the bank. AFS look at ML to advise whether a customer would continue with the bank or not? select 3 options.

Answer options:

A.Amazon ML uses logistic regression algorithm through Binary classification to solve the business problem
B.Amazon ML uses multi-nominal logistic regression algorithm through multi-classclassification to solve the business problem
C.Amazon ML uses linear regression algorithm through regression model to solve the business problem
D.Amazon ML uses Area Under the (Receiver Operating Characteristic) Curve (AUC) to provide accuracy of the model
E.Cross-validation is a technique for evaluating ML models by training several ML models on subsets of the available input data to detect overfitting which eventually fails to generalize the pattern
F.Amazon ML uses macro-average F1 score to provide accuracy of the model
G.Amazon ML uses standard root mean square error (RMSE) metric to provide accuracy of the model

Answer : A,D, E
Option A is correct - A. ML models for binary classification problems predict a binary outcome
https://docs.aws.amazon.com/machine-learning/latest/dg/types-of-ml-models.html
Option B is incorrect - ML models for multiclass classification problems allow you to generate predictions for multiple classes (predict one of more than two outcomes).
https://docs.aws.amazon.com/machine-learning/latest/dg/types-of-ml-models.html
Option C is incorrect -ML models for regression problems predict a numeric value.
https://docs.aws.amazon.com/machine-learning/latest/dg/types-of-ml-models.html
Option D is correct - Amazon ML provides an industry-standard accuracy metric for binary classification models called Area Under the (Receiver Operating Characteristic) Curve (AUC).
https://docs.aws.amazon.com/machine-learning/latest/dg/binary-model-insights.html
Option E is correct -Cross-validation is a technique for evaluating ML models by training several ML models on subsets of the available input data and evaluating them on the complementary subset of the data. Use cross- validation to detect overfitting
https://docs.aws.amazon.com/machine-learning/latest/dg/cross-validation.html
Option F is incorrect -The macro-average F1 score is used to evaluate the predictive accuracy of a multiclass metric.
https://docs.aws.amazon.com/machine-learning/latest/dg/multiclass-model-insights.html
Option G is incorrect - For linear regression tasks, Amazon ML uses the industry standard root mean square error (RMSE) metric.
https://docs.aws.amazon.com/machine-learning/latest/dg/regression-model-insights.html