Quiz: ML Basics Challenge


ML Basics ChallengeOnline version A quick machine learning quiz. by Karthi Keyan 1 What is overfitting in a model? a Model uses too little data b Model fits training data too well and fails on new data c Model ignores features d Model trains too fast 2 Which algorithm is typically used for linear regression? a K-means clustering b Decision tree c Ordinary least squares d Principal component analysis 3 What does a confusion matrix summarize? a Feature importances b True/false positives and negatives c Training loss over time d Hyperparameters 4 Which metric is best for imbalanced binary data? a Accuracy b AUC-ROC c Mean squared error d Fisher score 5 What is gradient descent used for? a Encoding categorical variables b Minimizing a loss function c Increasing model complexity d Clustering data 6 Which technique helps prevent overfitting? a Reducing data b Increasing epochs without change c Regularization d Using a smaller batch size only 7 What is a neural network primarily composed of? a Trees and leaves b Neurons with weights and activation functions c Support vectors d Clustering centers 8 Which learning paradigm uses labeled data? a Supervised learning b Semi-supervised learning c Reinforcement learning d Unsupervised learning 9 What is a common activation function? a Softmax always returns 1 b Exponential decay without threshold c ReLU d Binary step with dead neurons 10 Which method reduces dimensionality while preserving variance? a Boosting b PCA c KNN d Random forest

1

What is overfitting in a model?

a

Model uses too little data

b

Model fits training data too well and fails on new data

c

Model ignores features

d

Model trains too fast

2

Which algorithm is typically used for linear regression?

a

K-means clustering

b

Decision tree

c

Ordinary least squares

d

Principal component analysis

3

What does a confusion matrix summarize?

a

Feature importances

b

True/false positives and negatives

c

Training loss over time

d

Hyperparameters

4

Which metric is best for imbalanced binary data?

a

Accuracy

b

AUC-ROC

c

Mean squared error

d

Fisher score

5

What is gradient descent used for?

a

Encoding categorical variables

b

Minimizing a loss function

c

Increasing model complexity

d

Clustering data

6

Which technique helps prevent overfitting?

a

Reducing data

b

Increasing epochs without change

c

Regularization

d

Using a smaller batch size only

7

What is a neural network primarily composed of?

a

Trees and leaves

b

Neurons with weights and activation functions

c

Support vectors

d

Clustering centers

8

Which learning paradigm uses labeled data?

a

Supervised learning

b

Semi-supervised learning

c

Reinforcement learning

d

Unsupervised learning

9

What is a common activation function?

a

Softmax always returns 1

b

Exponential decay without threshold

c

ReLU

d

Binary step with dead neurons

10

Which method reduces dimensionality while preserving variance?

a

Boosting

b

PCA

c

KNN

d

Random forest

You can integrate the game into an LMS compatible with LTI 1.1 or LTI 1.3 such as Canvas, Moodle, or Blackboard. This way, the scores will be automatically saved into the platform’s gradebook.

ML Basics Challenge

Quiz

About this activity

Created by

Download the paper version to play

Top Games

Quiz

Spanish Alphabet Listening

Quiz

Photosynthesis vs Cellular Respiration - Practice Quiz

Quiz

Tissues - Practice Quiz

Quiz

UPS 5 Seeing Habits Quiz

Quiz

Practice Quiz - Punnett Square, Variation, and Mutations

ML Basics ChallengeOnline version

by Karthi Keyan

What is overfitting in a model?

Which algorithm is typically used for linear regression?

What does a confusion matrix summarize?

Which metric is best for imbalanced binary data?

What is gradient descent used for?

Which technique helps prevent overfitting?

What is a neural network primarily composed of?

Which learning paradigm uses labeled data?

What is a common activation function?

Which method reduces dimensionality while preserving variance?

		%
	Anonymous	%
		%
		%