Free Printable UNIT 1 MACHINE LEARNING INTRODUCTION ASSIGNMENT 1 QUIZ/FOUZIA

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UNIT 1 MACHINE LEARNING INTRODUCTION ASSIGNMENT 1 QUIZ/FOUZIA

Total questions: 25

Worksheet time: 12mins

Name

Class

Date

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

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

Which of the following is an example of unsupervised learning?

Linear regression

Decision tree

Clustering

Logistic regression

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

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.

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

Which algorithm is commonly used for classification in supervised learning?

The commonly used algorithm for classification in supervised learning is PCA.

The commonly used algorithm for classification in supervised learning is ANN.

The commonly used algorithm for classification in supervised learning is the Support Vector Machine (SVM).

The commonly used algorithm for classification in supervised learning is Linear Regression.

In unsupervised learning, which technique is used to reduce the dimensionality of the data?

Decision Tree

Linear Regression

K-means Clustering

Principal Component Analysis (PCA)

Which of the following is an application of supervised learning?

Anomaly detection

Face recognition

Market basket analysis

Density estimation

10.

What device below is not an example of Machine Learning?

Wearable fitness tracker

Google Assistant

Speech to Text

Google Search

None of the above

11.

What are the three types of Machine Learning? Choose three.

Supervised Learning

Learning Differentiated

Unsupervised Learning

Reinforcement Learning

Technical Learning

12.

What are the two types of Unsupervised Learning?

Loitering

Clustering

Association

Dissociation

13.

This type of Machine Learning learns by interacting with its environment. The agent receives rewards by performing correctly and penalties for performing incorrectly. The agent learns without intervention from a human by maximizing its reward and minimizing its penalty. It is a type of dynamic programming that trains algorithms using a system of reward and punishment.

Supervised Learning

Unsupervised Learning

Learning and Teaching

Reinforcement Learning

14.

Tom Mitchell of Carnegie Mellon University said that, "A computer program is said to learn from experience E with respect to some "T" and some performance measure P, if its performance on T, as measured by P, improves with experience E." What is "T"?

Time

Test

Task

Temper

15.

This picture shows a result of ...

Supervised Learning: Classification

Unsupervised Learning: Regression

Unsupervised Learning: Prediction

Supervised Learning: Regression

16.

This picture shows an application of ...

Supervised Learning: Classification

Unsupervised Learning: Clustering

Unsupervised Learning: Prediction

Supervised Learning: Regression

17.

What is the goal of clustering?

Group similar instances

Predict numerical values for testing examples

Reduce the number of features

None of the above

18.

Which method is used to split data into train and test sets in Python?

split_data()

train_test_split()

data_divider()

random_split()

19.

What is the equation of Simple Linear Regression?

y = mx + c

y = a² + bx + c

y = log(x)

y = sin(x)

20.

What does Entropy measure in a Decision Tree?

Accuracy

Purity of a split

Height of the tree

Number of leaves

21.

What is a common problem if a Decision Tree grows too deep?

Underfitting

Overfitting

High Bias

Low Variance

22.

PCA helps in:

Data Collection

Dimensionality Reduction

Overfitting

Model Evaluation

23.

Which of the following are classification tasks (Multiple Correct)?

Predicting the outcome of an election

Predicting the weight of a giraffe based on its weight

Predicting the emotion conveyed by a sentence

Identifying abnormal data points

24.

Which of the following are supervised learning problems (Multiple Correct)?

Clustering Spotify users based on their listening history

Weather forecast using data collected by a satellite

Predicting tuberculosis using patient’s chest X-Ray

Training a humanoid to walk using a reward system

25.

Data preprocessing involves:

Training the model

Cleaning and transforming data

Deploying models

Writing reports

Reset

UNIT 1 MACHINE LEARNING INTRODUCTION ASSIGNMENT 1 QUIZ/FOUZIA

Total questions: 25

Worksheet time: 12mins

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