MCA(QUIZ)

MCA(QUIZ)

University

8 Qs

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MCA(QUIZ)

MCA(QUIZ)

Assessment

Quiz

Computers

University

Medium

Created by

Syedzoofa Rufai

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8 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following best defines Artificial Intelligence (AI)?

Use of computers for arithmetic operations

The science of making machines mimic human intelligence

Programming a system without logic

Automating hardware functions

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which one of the following best describes declarative knowledge?

Sequence of operations to achieve a task

Facts and assertions that describe the world

Knowledge derived from procedures

Knowledge about memory allocation

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

A machine learning task that predicts a numeric output is called:

Classification

Clustering

Regression

Dimensionality Reduction

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In Linear Regression, what is the role of the cost function?

To measure the error between predicted and actual values

To compute the accuracy of classification

To choose the best data points

To calculate gradients for neural networks

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What happens if the learning rate in Gradient Descent is too high?

The algorithm converges slowly

The cost function is minimized efficiently

The algorithm may overshoot and fail to converge

The slope becomes zero

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following mathematical concepts is essential for computing relationships in multi-variable machine learning models?

Set Theory

Boolean Algebra

Calculus only

Matrix Theory

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is an example of unsupervised learning?

Predicting house prices

Classifying emails as spam or not spam

Clustering similar customer profiles

Diagnosing disease based on symptoms

8.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary goal of applying Gradient Descent in Linear Regression?

To choose the best classification algorithm

To eliminate outliers

To minimize the cost function and find optimal weights

To increase the number of features