🏆 Machine Learning Final Test

⏱️ 35 min 📚 Final Exam 🎯 Pass: 70%
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Question 1 of 18

Which Of These Is An Example Of A Machine Learning Task?

A
Hard-coding if-then rules for identifying spam
B
Training a model with labeled photos to recognize objects
C
Randomly guessing labels for data
D
Writing a program that calculates 2+2

Question 2 of 18

Machine Learning Finds Patterns From ______ Rather Than Explicit Instructions.

A
Algorithms
B
Data
C
Models
D
Predictions

Question 3 of 18

Which Scenario Is An Example Of Unsupervised Learning?

A
A model trained on labeled cat/dog images
B
A robot learning to play a game through rewards
C
Grouping news articles by topic without labels
D
Training a spam filter with labeled emails

Question 4 of 18

In Supervised Learning, The Provided Correct Answers Are Called ______.

A
Labels
B
Features
C
Datasets
D
Parameters

Question 5 of 18

Which Problem Is An Example Of Regression?

A
Classifying emails as spam or not
B
Predicting tomorrow's temperature
C
Grouping animals into species
D
Training a chatbot through conversation

Question 6 of 18

When Each Example's Output Is A Numeric Value, The Machine Learning Task Is Called ______.

A
Classification
B
Prediction
C
Clustering
D
Regression

Question 7 of 18

Which Of These Is A Feature In A Machine Learning Dataset For Predicting Car Prices?

A
The predicted price
B
The car's mileage
C
The model's overall accuracy
D
The size of the training set

Question 8 of 18

Each Row In A Dataset (With Features And A Label) Is Called An ______ Or Example.

A
Instance
B
Algorithm
C
Model
D
Parameter

Question 9 of 18

Why Do We Use A Separate Test Set In Machine Learning?

A
To make training faster
B
To reduce the number of features
C
To provide ground truth labels during training
D
To get an unbiased performance on new data

Question 10 of 18

We Split The Data Into Training And Test Sets To Evaluate How Well The Model Can ______ To New Data.

A
Memorize
B
Generalize
C
Overfit
D
Train

Question 11 of 18

If A Model Gets 100% Accuracy On Training Data But Only 50% On New Data, This Model Is:

A
Underfitting
B
Overfitting
C
Perfect
D
Suffering from data leakage

Question 12 of 18

A Model That Is Too Simple And Cannot Capture The Underlying Pattern Is Experiencing ______.

A
Underfitting
B
Overfitting
C
Bias
D
Variance

Question 13 of 18

Which Metric Measures The Fraction Of Actual Positive Examples That The Model Correctly Identified?

A
Accuracy
B
Precision
C
Recall
D
F1 Score

Question 14 of 18

In Classification, Precision Tells Us How Many Predicted Positives Were Correct, While ______ Tells Us How Many Actual Positives Were Found.

A
Accuracy
B
Recall
C
F1 Score
D
Error Rate

Question 15 of 18

Which Of These Is An Example Of Dataset Bias Affecting A Model?

A
A face ID app making errors on certain skin tones
B
A weather model missing data for one region
C
A recommender system showing only popular items
D
An app that runs slower on older phones

Question 16 of 18

If A Model Systematically Favors One Group Over Another, This Indicates An Issue Of ______.

A
Bias
B
Variance
C
Overfitting
D
Accuracy

Question 17 of 18

Which Approach Is Likely To Help A Model That Is Underfitting?

A
Reduce the number of features
B
Increase model complexity
C
Remove more training data
D
Decrease the number of training iterations

Question 18 of 18

Adjusting A Model's Settings (Like Learning Rate Or Tree Depth) To Improve Performance Is Called Hyperparameter ______.

A
Training
B
Testing
C
Tuning
D
Fitting
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