15 Questions
What optimization objective maximizes the area under the receiver operating characteristic curve (AUC ROC) value?
Maximizing the area under the receiver operating characteristic curve
In the context of a video sharing website, what is a good measure to determine the success of an ML model predicting popular videos?
Predicting 95% of the most popular videos measured by watch time within 30 days of being uploaded
What should be done to assist gradient optimization when dealing with columns of data having different ranges in a Neural Network project?
Use representation transformation (normalization) technique
What method can be used to eliminate features that do not provide a strong signal in a model?
Lasso regression
Which Google Cloud tool can be used to determine the impact of excluding individual features on model performance?
What-If tool
What function in BigQuery can be used to calculate the Pearson correlation coefficient between features and the target variable?
CORR()
In a highly skewed dataset where examples without the company's logo are dominant, which metric would be most suitable to evaluate a classification model?
Precision-Recall Curve
Which metric places more emphasis on the ability of the model to capture all positive instances, given a dataset highly imbalanced towards one class?
F1 Score
What technique can be used to obtain feature attributions from a model by submitting prediction requests with a specific keyword?
'explain' keyword in BigQuery
What approach should you take when building a regression model to minimize effort and training time while maximizing model performance?
Use AutoML Tables to train the model without early stopping
In a linear model with over 100 input features, all with values between –1 and 1, what technique is suitable to remove non-informative features?
Use L1 regularization to reduce the coefficients of uninformative features to 0
If you suspect that many features are non-informative in your model, what should you do to keep the informative ones while removing the non-informative ones?
Utilize L1 regularization to eliminate non-informative features
When building a regression model, what method can you use to identify which features do not degrade the model when removed?
Use an iterative dropout technique to assess feature importance
In a high-dimensional dataset with potentially non-informative features, what strategy helps differentiate informative from non-informative features?
Using recursive feature elimination (RFE) with cross-validation for ranking features
Which method is most suitable for identifying the least informative features in a regression model and discarding them?
Employing L2 regularization to penalize unimportant features
This quiz covers using AI Platform notebooks for Lasso regression analysis, streaming prediction results to BigQuery, calculating Pearson correlation coefficients with BigQuery's CORR function, and utilizing the AI Explanations feature for feature attributions using the sampled Shapley method.
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