You want to evaluate the relationship between feature values and target variables. You have a
large number of observations having a near uniform distribution and the features are highly
correlated.
Which model explanation technique should you choose?
You have created a Data Science project in a compartment called Development and shared it
with a group of collaborators. You now need to move the project to a different compartment called
Production after completing the current development iteration.
Which statement is correct?
As a data scientist, you create models for cancer prediction based on mammographic images.
The correct identification is very crucial in this case. After evaluating two models, you arrive at the
following confusion matrix.
Model 1 has Test accuracy is 80% and recall is 70%.
* Model 2 has Test accuracy is 75% and recall is 85%.
Which model would you prefer and why?
As a data scientist, you are working on a global health data set that has data from more than 50 countries. You want to encode three features, such as 'countries', 'race', and 'body organ' as categories. Which option would you use to encode the categorical feature?
As a data scientist, you are trying to automate a machine learning (ML) workflow and have
decided to use Oracle Cloud Infrastructure (OCI) AutoML Pipeline.
Which three are part of the AutoML Pipeline?
