Exploring Machine Learning Concepts

Exploring Machine Learning Concepts

University

8 Qs

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Exploring Machine Learning Concepts

Exploring Machine Learning Concepts

Assessment

Quiz

Computers

University

Practice Problem

Medium

Created by

fathima haqul

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8 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is supervised learning?

Supervised learning is a machine learning approach that uses labeled data to train models.

Supervised learning is a type of reinforcement learning.

Supervised learning is a method that requires no data for training.

Unsupervised learning uses labeled data to train models.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is an example of supervised learning?

Identifying patterns in stock market trends.

Clustering customer data based on purchase history.

Predicting whether an email is spam or not.

Segmenting images into different categories.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main goal of unsupervised learning?

To classify data into predefined categories.

To predict future outcomes based on past data.

To enhance the accuracy of labeled datasets.

To identify patterns or structures in data without labeled responses.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does clustering differ from classification?

Clustering analyzes data based on time; classification focuses on spatial data.

Clustering groups data without labels; classification assigns labels based on known categories.

Clustering is a supervised learning technique; classification is unsupervised.

Clustering requires predefined categories; classification does not.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are neural networks primarily used for?

Image recognition, natural language processing, and predictive analytics.

Data entry, email marketing, and graphic design.

Social media management, video editing, and web design.

Weather forecasting, stock trading, and game development.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the role of activation functions in neural networks?

Activation functions enable neural networks to learn non-linear relationships.

Activation functions help in reducing the size of the neural network.

Activation functions are responsible for data preprocessing before training.

Activation functions are used to initialize weights in neural networks.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Can you name a common algorithm used in supervised learning?

Support Vector Machine

K-Means Clustering

Linear Regression

Decision Tree

8.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What type of data does unsupervised learning typically work with?

Structured data

Unlabeled data

Supervised data

Labeled data