Quiz: ML Quick Quiz


ML Quick QuizOnline version Test your ML knowledge. by Dr.Sambath kumar 1 What does ML stand for in computer science? a Multilayer Logic b Micro Logic c Model Leasing d Machine Learning 2 Which algorithm is commonly used for supervised classification? a Principal Component Analysis b Apriori Algorithm c Support Vector Machine d K-means Clustering 3 What is overfitting in machine learning? a Model underfits training data b Model fits training data too closely and generalizes poorly c Model never trains d Model uses too many features 4 Which metric is often used for binary classification evaluation? a Mean Squared Error b Accuracy or AUC c Calinski-Harabasz Index d Silhouette Score 5 Which learning paradigm uses labeled data? a Supervised learning b Unsupervised learning c Reinforcement learning d Self-supervised learning 6 What is a common method to prevent overfitting in neural networks? a Regularization (e.g., dropout) b Increasing learning rate c Batch normalization only d Using fewer layers 7 Which algorithm is typically used for clustering unlabeled data? a Linear Regression b K-means c Decision Tree d Logistic Regression 8 What is gradient descent used for? a Evaluating model performance b Optimizing model parameters by minimizing a loss function c Splitting datasets d Sampling data 9 Which activation function is common in neural networks? a Sigmoid b ReLU c Tanh without scaling d Softmax with cross-entropy only 10 What is the purpose of a validation set? a Train the model b Compute training loss only c Tune hyperparameters and monitor generalization d Test final performance

1

What does ML stand for in computer science?

a

Multilayer Logic

b

Micro Logic

c

Model Leasing

d

Machine Learning

2

Which algorithm is commonly used for supervised classification?

a

Principal Component Analysis

b

Apriori Algorithm

c

Support Vector Machine

d

K-means Clustering

3

What is overfitting in machine learning?

a

Model underfits training data

b

Model fits training data too closely and generalizes poorly

c

Model never trains

d

Model uses too many features

4

Which metric is often used for binary classification evaluation?

a

Mean Squared Error

b

Accuracy or AUC

c

Calinski-Harabasz Index

d

Silhouette Score

5

Which learning paradigm uses labeled data?

a

Supervised learning

b

Unsupervised learning

c

Reinforcement learning

d

Self-supervised learning

6

What is a common method to prevent overfitting in neural networks?

a

Regularization (e.g., dropout)

b

Increasing learning rate

c

Batch normalization only

d

Using fewer layers

7

Which algorithm is typically used for clustering unlabeled data?

a

Linear Regression

b

K-means

c

Decision Tree

d

Logistic Regression

8

What is gradient descent used for?

a

Evaluating model performance

b

Optimizing model parameters by minimizing a loss function

c

Splitting datasets

d

Sampling data

9

Which activation function is common in neural networks?

a

Sigmoid

b

ReLU

c

Tanh without scaling

d

Softmax with cross-entropy only

10

What is the purpose of a validation set?

a

Train the model

b

Compute training loss only

c

Tune hyperparameters and monitor generalization

d

Test final performance

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 Quick Quiz

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ML Quick QuizOnline version

by Dr.Sambath kumar

What does ML stand for in computer science?

Which algorithm is commonly used for supervised classification?

What is overfitting in machine learning?

Which metric is often used for binary classification evaluation?

Which learning paradigm uses labeled data?

What is a common method to prevent overfitting in neural networks?

Which algorithm is typically used for clustering unlabeled data?

What is gradient descent used for?

Which activation function is common in neural networks?

What is the purpose of a validation set?

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