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AI and Machine Learning

Total questions: 26

Worksheet time: 16mins

Name
Class
Date
1.

The main goal of the "Classifying Fish" activity is to ________, and the data used is ________.

a)

identify fish species using observable characteristics

b)

teach fish anatomy using genetic data

c)

track fish migration using satellite data

d)

study fish behavior using experimental data

2.

What do "feature" and "label" mean in machine learning?

a)

A feature is an input variable used to make predictions, while a label is the output or target variable that the model tries to predict.

b)

A feature is the output variable, and a label is the input variable in a machine learning model.

c)

A feature and a label are both output variables in a machine learning model.

d)

A feature and a label are both input variables in a machine learning model.

3.

How do humans influence the training of a machine learning model?

a)

Selecting and preparing the training data

b)

Letting the model train without supervision

c)

Ignoring the model's results

d)

Stopping the model from learning

4.

What is the difference between Supervised and Unsupervised machine learning? Give a simple analogy.

a)

Supervised learning uses labeled data like a teacher guiding students, while unsupervised learning uses unlabeled data like students grouping themselves.

b)

Supervised learning uses unlabeled data like students grouping themselves, while unsupervised learning uses labeled data like a teacher guiding students.

c)

Both use labeled data, but supervised learning is faster.

d)

Unsupervised learning is only for regression, supervised learning is for clustering.

5.

What was surprising about training a model with all features versus just one important feature in the AI Lab activity?

a)

Using all features did not always improve performance compared to using one important feature.

b)

Using all features always gave the best performance.

c)

Using one feature always gave poor accuracy.

d)

Using all features made training faster than using one feature.

6.

What are the main steps to create a machine learning application?

a)

Collect data, train model, deploy application

b)

Design user interface, write documentation, test application

c)

Gather requirements, code application, release update

d)

Select hardware, install software, monitor performance

7.

The goal of the "Classifying Fish" activity is to train an A.I. bot to identify fish and help clean the ocean. This is done by labeling images as either ______ or ______.

a)

Fish; Not Fish

b)

Fish; Trash

c)

Marine; Non-Marine

d)

Ocean; Land

8.

In machine learning, which of the following best describes a "feature"?

a)

The output the model predicts

b)

The input used for decisions

c)

The name of the shape

d)

The dataset used for training

9.

What is a Decision Tree used for in machine learning?

a)

A Decision Tree helps make decisions by asking a series of questions.

b)

A Decision Tree stores large amounts of data.

c)

A Decision Tree encrypts information.

d)

A Decision Tree generates random numbers.

10.

What does a model card include?

a)

Intended Use, Limitations and Warnings

b)

Training Data, Hyperparameters, Loss Functions

c)

Source Code, API Documentation, User Reviews

d)

Hardware Requirements, Network Topology, Security Protocols

11.

Who chooses the features for training a machine learning model?

a)

The computer

b)

The dataset

c)

Humans

d)

The model card

12.

What are the three steps in the machine learning process?

a)

Data, Model, App

b)

Input, Output, Feedback

c)

Training, Testing, Deployment

d)

Feature, Label, Prediction

13.

AI models can have unintended negative consequences. What is model accuracy and how can AI be misused?

a)

Model accuracy is how well an AI predicts outcomes, and misuse can cause ethical, social, or safety risks.

b)

Model accuracy is unrelated to harm or misuse in AI.

c)

AI models are always accurate and cannot be misused.

d)

Model accuracy only affects AI speed, not harm.

14.

Fill in the blank: ________ measures how often a model's predictions are correct.

a)

Accuracy

b)

Precision

c)

Recall

d)

Loss

15.

Fill in the blank: ________ is technology that lets computers do tasks that usually need human intelligence, like recognizing images and translating languages.

a)

AI (Artificial Intelligence)

b)

CPU (Central Processing Unit)

c)

RAM (Random Access Memory)

d)

HTML (HyperText Markup Language)

16.

Fill in the blank: ________ is a machine learning problem where the model categorizes data into predefined classes, like labeling an image as 'Fish' or 'Not Fish.'

a)

Classification

b)

Regression

c)

Clustering

d)

Dimensionality Reduction

17.

Fill in the blank: ________ is a model that makes decisions using a flowchart of questions and answers.

a)

Decision Tree

b)

Linear Regression

c)

Neural Network

d)

Random Forest

18.

Fill in the blank: ________ is an input that helps the model make decisions. For example, in a restaurant recommender, features could be toppings like pepperoni or peppers.

a)

Feature

b)

Label

c)

Algorithm

d)

Output

19.

Fill in the blank: ________ is what a model tries to predict. For example, in a shoe recommender, the 'shoe' is the label.

a)

Label

b)

Feature

c)

Input

d)

Parameter

20.

Fill in the blank: The process by which a computer learns from data to make decisions or predictions is called _________.

a)

Machine Learning

b)

Data Entry

c)

Manual Programming

d)

Hardware Engineering

21.

Fill in the blank: A document that explains a machine learning model’s purpose, training, and limitations is called a _________?

a)

Model Card

b)

Data Sheet

c)

Performance Report

d)

Training Log

22.

Fill in the blank: Predicting user preferences and suggesting items like books or shoes is called a _________.

a)

Recommendation

b)

Classification

c)

Regression

d)

Clustering

23.

Which of the following is an example of categorical data rather than numerical data?

a)

The number of minutes each student spends on homework

b)

The temperature outside in degrees Fahrenheit

c)

The types of pets students have at home

d)

The heights of students measured in inches

24.

What is the difference between artificial intelligence and machine learning?

4 lines
25.

Which of the following is a common task performed by machine learning models?

a)

Drawing pictures

b)

Sending emails automatically

c)

Predicting outcomes based on data

d)

Building websites

26.

What is the purpose of training a machine learning model?

a)

To help the model learn patterns from data

b)

To create new hardware

c)

To design user interfaces

d)

To write documentation