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Exploring Machine Learning Concepts

Authored by Chairman, Media and PR Committee NITTTR Chandigarh

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Exploring Machine Learning Concepts
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15 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main goal of supervised learning?

To train a model on labeled data for accurate predictions.

To generate new data points from existing data.

To classify data without any labels.

To reduce the size of the dataset for faster processing.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which algorithm is commonly used for classification tasks in supervised learning?

Principal Component Analysis

K-Means Clustering

Linear Regression

Logistic Regression

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What distinguishes unsupervised learning from supervised learning?

Both unsupervised and supervised learning use labeled data.

Unsupervised learning does not use labeled data, while supervised learning does.

Unsupervised learning is only applicable to classification tasks.

Unsupervised learning requires labeled data, while supervised learning does not.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Name a common application of clustering in unsupervised learning.

Data normalization

Market analysis

Feature extraction

Customer segmentation

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a neural network primarily used for?

Data storage solutions

Web development frameworks

Graphic design tools

Neural networks are primarily used for machine learning tasks.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How do neurons in a neural network communicate?

Neurons do not communicate with each other in a neural network.

Neurons communicate by exchanging physical objects.

Neurons communicate by sending chemical signals only.

Neurons communicate by passing signals through weighted connections and activating based on input.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of activation functions in neural networks?

To increase the speed of training in neural networks.

The purpose of activation functions in neural networks is to introduce non-linearity and enable the network to learn complex patterns.

To reduce the number of layers in a neural network.

To ensure all outputs are between 0 and 1.

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