Introduction to Machine Learning

Introduction to Machine Learning

University

12 Qs

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Introduction to Machine Learning

Introduction to Machine Learning

Assessment

Quiz

Mathematics

University

Practice Problem

Hard

Created by

Mahesh Divakaran

Used 7+ times

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12 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary characteristic of supervised learning?

Supervised learning only works with images
Supervised learning requires labeled training data to make predictions or decisions.
Supervised learning does not require any training data
Unlabeled training data is used for making predictions

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In supervised learning, what is the role of the model during training?

Learn from the input data and adjust its parameters to minimize the difference between its predicted output and the actual output.

Maximize the difference between its predicted output and the actual output

Ignore the input data and focus on its initial parameters

Generate random outputs without learning from the input data

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is an example of unsupervised learning?

Linear regression
Decision tree
Clustering
Logistic regression

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main goal of clustering algorithms in unsupervised learning?

To predict future outcomes based on historical data

Group similar data points together based on certain features or characteristics.

To classify data into predefined categories
To identify outliers in the dataset

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Semi-supervised learning combines elements of both:

Semi-supervised learning combines elements of both reinforcement learning and deep learning.
Semi-supervised learning combines elements of both classification and clustering.
Semi-supervised learning combines elements of both supervised and unsupervised learning.
Semi-supervised learning combines elements of both regression and dimensionality reduction.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which statement is true about semi-supervised learning?

Semi-supervised learning only uses labeled data for training
Semi-supervised learning uses a combination of labeled and unlabeled data for training.
Semi-supervised learning does not require any data for training
Semi-supervised learning is only suitable for image recognition tasks

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of a validation set in supervised learning?

Training the model

Testing the model on unseen data

Providing additional labeled data

Tuning hyperparameters

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