Transform your business >> How Google does Machine Learning
TOTAL POINTS 3
1.Which of the following scenarios may require a supervised learning model to be retrained as a new model?
1 point
The model was trained on labeled data and we now wish to train it on more to label the data
The model was trained on unlabeled data and we now wish to add labels to the data.
The model was trained on labeled data and we now wish to correct the labels of the data.
2.A team is preparing to develop and deploy an ML model for use on a shopping website. They have collected a little data to train the model. The team plans on gathering more data once the model is developed. Now they are ready for the next phase, training.
Which of these scenarios will most likely lead to a successful deployment of the ML model?
1 point
The team should take time to focus on training the perfect model, because deployment is quick and easy.
The team should take time to gather more data because the quality and architecture of the model are affected by the amount of data
The team should focus on deployment of the model. The model can be weak to start, then be improved when more user data has been accumulated.
3.An online shopping company has a team of customer representatives read emails from customers. Depending upon the content of the email, the representative routes the email to the appropriate department.
The company would like to alleviate the customer representatives task by automating it. Your team has been asked to create an app to read customer emails and determine which department should handle it.
Which of these would be a good way to structure the app (choose all that apply)?
1 point
The team should develop one all-encompassing model that will scan the email content, categorize the content, and determine the appropriate team to receive the email.
The team should develop several models, one for each task. They should develop these models from the ground up and not use pre-existing models, to ensure the models are properly trained.
Automatic feature extraction
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