Coursera Microsoft Azure Data Scientist Associate (DP-100) • STUDY MODE
Quiz: Create machine learning models
QUESTION 1 OF 13
Your manager has asked you to create a binary classification model to predict whether a person has a disease. You need to detect possible classification errors.
A
False positives
B
False negatives
C
True negativesCorrect Answer
D
True positives
QUESTION 2 OF 13
You are a senior data scientist in the company and you are tasked with evaluating a completed binary classification machine learning model.
You are a data scientist of a company and you are tasked with building a deep convolutional neural network (CNN) for image classification. The CNN model you built shows signs of overfitting. You need to reduce overfitting and converge the model to an optimal fit.
A
Add an additional dense layer with 64 input units
B
Reduce the amount of training data
C
Add an additional dense layer with 512 input units
D
Add L1/L2 regularizationCorrect Answer
E
Use training data augmentationCorrect Answer
QUESTION 4 OF 13
Your manager has provided you a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features. You use 75 percent of the data points for training and 25 percent for testing.
A
Box1: PCA(n_components=10000);
B
Box2: pca;
C
Box3: X_train
D
Box1: PCA(n_components=10);
E
Box2: model;
F
Box3: transform(x_test)
G
Box1: PCA(n_components=150);
H
Box3: x_test
QUESTION 5 OF 13
You are creating a model to predict the price of a student’s artwork depending on the following variables: the student’s length of education, degree type, and art form.
A
Yes
B
NoCorrect Answer
QUESTION 6 OF 13
What happens when a NumPy array is multiplied by 5?
A
Array stays the same size, but each element is multiplied by 5.Correct Answer
B
The new array will be 5 times longer, with the sequence repeated 5 times.
C
The new array will be 5 times longer, with the sequence repeated 5 times and also all the elements are multiplied by 5.
QUESTION 7 OF 13
You are creating a model and you want to evaluate it. One metric yields an absolute metric in the same unit as the label.
A
Root Mean Square Error (RMSE)Correct Answer
B
Coefficient of Determination (known as R-squared or R2)
C
Mean Square Error (MSE)
QUESTION 8 OF 13
Complete the sentence:
A
Regression
B
ClassificationCorrect Answer
C
Clustering
QUESTION 9 OF 13
It is well known that Python provides extensive functionality with powerful and statistical numerical libraries. What is TensorFlow useful for?
A
Offering simple and effective predictive data analysisCorrect Answer
B
Supplying machine learning and deep learning capabilities
C
Providing attractive data visualizations
D
Analyzing and manipulating data
QUESTION 10 OF 13
You are creating a binary classification by using a two-class logistic regression model. You need to evaluate the model results for imbalance. Which evaluation metric should you use?
A
Relative Squared Error
B
Mean Absolute Error
C
Relative Absolute Error
D
AUC CurveCorrect Answer
QUESTION 11 OF 13
What happens when a list is multiplied by 5?
A
The new list remains the same size, but the elements are multiplied by 5.
B
The new list created has the length 5 times the original length with the sequence repeated 5 times and also all the elements are also multiplied by 5.
C
The new list created has the length 5 times the original length with the sequence repeated 5 times.Correct Answer
QUESTION 12 OF 13
You are tasked to analyze a dataset containing historical data from a local taxi company. You are developing a regression model for this. Your goal is to predict the fare of a taxi trip. You need to select performance metrics to correctly evaluate the regression model.
A
An F1 score that is low
B
An R-Squared value close to 0
C
An R-Squared value close to 1Correct Answer
D
A Root Mean Square Error value that is lowCorrect Answer
QUESTION 13 OF 13
You are creating a model and you want to evaluate it. For this, you take a look on a specific metric which is direct proportional with how well the model fits.
A
Mean Square Error (MSE)
B
Coefficient of Determination (known as R-squared or R2)Correct Answer
C
Root Mean Square Error (RMSE)
Ready to test your recall?
Your manager has asked you to create a binary classification model to predict whether a person has a disease. You need to detect possible classification errors.