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Machine Learning and Neural Networks

Total questions: 50

Worksheet time: 25mins

Name
Class
Date
1.

What is a feature in machine learning?

a)

A program that runs the dataset

b)

A characteristic that describes an object

c)

A rule that controls the computer

d)

A picture that shows the results

2.

In a tabular dataset, what does each column represent?

a)

A place to store images only

b)

A particular feature of the data

c)

A single example in the dataset

d)

A step in a computer program

3.

In a table of a dataset, what does each row correspond to?

a)

A computer hardware part

b)

An example in the dataset

c)

A random number generator

d)

A feature name list

4.

In the ML4K pipeline, what is the first step shown in the diagram?

a)

Use the model

b)

Test the model

c)

Train a classifier

d)

Collect your data

5.

Which step comes immediately after you label each item to a class in the ML4K pipeline?

a)

Use the model in a system

b)

Design a feature set

c)

Train a classifier

d)

Collect your data

6.

A team has collected pictures and chosen features like body type and fin color. What should they do next to build the dataset, according to the diagram?

a)

Skip straight to training

b)

Use the model in a game

c)

Immediately test the model

d)

Code the data using the feature set

7.

Which source is a valid way to collect data shown in the image?

a)

Stories remembered without checking

b)

Random numbers made by guessing

c)

Opinions guessed without asking

d)

Sensors in a car tracking speed

8.

A dataset is split into two parts before training a model. Which pair correctly names these parts and shows their typical sizes?

a)

Training set ninety percent, test set ten percent

b)

Training set ten percent, test set ninety percent

c)

Training set half, test set half

d)

Training set seventy percent, test set thirty percent

9.

What does the algorithm do with the training data during model building?

a)

Finds patterns called statistical correlations

b)

Randomly guesses without using features

c)

Deletes half of the examples to simplify

d)

Changes labels to match the features

10.

After a model is trained, what is the next step to check how well it works?

a)

Test the model using the test set for accuracy

b)

Add more features without checking results

c)

Split the training set again into two sets

d)

Ignore testing because training is enough

11.

Which AI tool helps with talking and listening tasks?

a)

Face detection at a party

b)

License plate readers for cars

c)

Self-driving car dashboard view

d)

Intelligent assistants like smart speakers

12.

Why do neural networks often work better for hard problems like understanding images?

a)

They need very little data always

b)

They create their own helpful features

c)

They only explain decisions clearly

d)

They use simple yes-or-no rules

13.

What is one advantage of decision trees?

a)

They require less data to train

b)

They drive cars by themselves

c)

They detect faces in pictures

d)

They build their own features

14.

Look at the diagram showing circles connected by arrows. What are the circles called in a neural network?

a)

units or neurons

b)

inputs or outputs

c)

weights or biases

d)

links or cables

15.

In the layered diagram, which layer sends the final numbers out of the network?

a)

Output layer

b)

Input layer

c)

Starter layer

d)

Middle layer

16.

A unit takes several numbers and makes one number. Which part controls how strongly each input affects that unit?

a)

Input dots

b)

Weighted connections

c)

Output arrows

d)

Hidden circles

17.

Look at the two diagrams: one shows a biological neuron with parts like dendrites and axon, and the other shows an artificial neuron with inputs X1, X2, X3 leading to an output. What idea do both diagrams share?

a)

Both pass signals from inputs to outputs

b)

Both store pictures in memory forever

c)

Both decide using only random guessing

d)

Both work without any connections at all

18.

In the network diagram with an input layer, three hidden layers, and an output layer, what makes it a deep neural network?

a)

It uses one giant output neuron

b)

It has many connected hidden layers

c)

It removes the input layer completely

d)

It has no wires between any layers

19.

In a simple linear unit, what happens to each input before the results are added?

a)

It is turned into a binary number

b)

It is ignored by the summation circle

c)

It is multiplied by the weight value

d)

It is divided by the weight value

20.

Which formula shows the summation for two inputs and two weights?

a)

x1 × x2 + w1 × w2 = y

b)

x1 × w1 + x2 × w2 = y

c)

x1 + w1 + x2 + w2 = y

d)

x1 − w1 + x2 − w2 = y

21.

A linear threshold unit gives a binary output. What does binary mean here?

a)

Three choices, 0, 1, or 2

b)

Two choices, either 0 or 1

c)

Many choices from zero to nine

d)

Only one choice, always 1

22.

What does a learning algorithm change in a neural network to help it perform better?

a)

The weights connecting inputs

b)

The size of the classroom

c)

The colors of the graphs

d)

The number of school subjects

23.

Which best describes a feature vector in simple terms?

a)

A schedule of homework

b)

A picture of a robot

c)

A single final answer

d)

A list of input features

24.

Why do many AI apps use artificial neural networks?

a)

They stop cars from moving

b)

They work only with one neuron

c)

They erase all memories

d)

They can learn from data

25.

Which statement best shows the meaning of inclusive OR in everyday language?

a)

You choose a or b, possibly both

b)

You choose a or b, but not both

c)

You must choose both a and b together

d)

You cannot choose a or b at any time

26.

In a PBJ sandwich rule "peanut butter AND jelly," when is the rule true?

a)

True if you have peanut butter only

b)

True if you have jelly only

c)

True if you have both peanut butter and jelly

d)

True if you have neither ingredient

27.

Which situation matches an OR rule from the image?

a)

Joe likes ketchup and mustard on his hamburger

b)

A car needs both headlights and brake lights

c)

I should wear my boots if it’s raining or snowing

d)

A PBJ sandwich requires peanut butter and jelly

28.

If Luisa wants to get a cat OR a dog, which choice makes the OR statement true?

a)

She gets only a cat as her pet

b)

She gets both a cat and a dog

c)

She gets neither pet at all

d)

She gets only a fish as her pet

29.

There are three fundamental operations in Boolean Algebra: ______

a)

Addition, Subtraction and Multiplication

b)

NOT, AND, and OR

c)

IF, AND, and BUT

d)

IF, ELSE, and ELSE IF

30.

A NOT takes a single Boolean value, either true or false, and ______

a)

makes it true

b)

makes it false

c)

negates it

d)

keeps it the same

31.

For the AND Boolean operation, the output is only true if _____

a)

one input is true

b)

one input is false

c)

both inputs are true

d)

both inputs are false

32.

What is A.I?

a)

Intelligence demonstrated by machines

b)

Smart robots

c)

Anthony Ian

d)

I don't know

33.

How does A.i work?

a)

Combining large amounts of data with fast processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data.

b)

The computation, mostly on computers, of antiderivatives and definite integrals in term of formulas

c)

It just works you know??

d)

Another super duper long answer to fool you guys to prove that not all longest answers are the correct ones, how is my quiz going anyway, i hope it is good, hope it is not too long though, thank you for not clicking

34.

What is this?

a)

artificial intelligence

b)

algorithm

c)

neural network

35.

Which one of these is not an area of AI?

a)

computer vision/image recognition

b)

voice recognition

c)

web design

d)

robotics

36.

How many images would you need of a cat, for example, to train a neural network ?

a)

about 10

b)

a few hundred

c)

thousands

37.

It is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed

a)

Artificial Intelligence

b)

Decision Tree

c)

Machine Learning

d)

Linear Regression

38.

Which is the correct structure of a Neural Network?

a)

Output, Hidden Layer, Input

b)

Hidden Layer, Input, Output

c)

Input, Hidden Layer, Output

39.

This is where we insert the initial data for the neural network.

a)

Input

b)

Hidden Layer

c)

Output

40.

This is an intermediate layer between input and output layer and place where all the computation is done.

a)

Input

b)

Hidden Layer

c)

Output

41.

It produces the result for given inputs.

a)

Input

b)

Hidden Layer

c)

Output

42.

from the picture, what kind of programming is it?

a)

Traditional Programming

b)

Modern Programming

c)

Machine Learning

d)

Traditional Learning

43.

from the picture, what kind of programming is it?

a)

Traditional Programming

b)

Machine Learning

c)

Modern Programming

d)

Traditional Learning

44.

The modern Turing test to tell computers and humans apart, is commonly abbreviated as ___

a)

APTCHA

b)

PACTCHA

c)

CAPTCHA

d)

CACPHAT

45.

What do you call the feature that checks you are not a robot / hacking program?

a)

Captcha

b)

Proover

c)

Tester

d)

Grabber

46.

Most advanced form of Artificial Intelligence is:

a)

Deep Learning is the most advanced form of Artificial Intelligence.

b)

Artificial Intelligence covers all the concepts and algorithms which, in some way or the other mimic human intelligence.

c)

Machine learning is the most advanced form of Artificial Intelligence.

47.

What is Deep learning?

a)

A variation of neural networks where many layers are used in the network to solve a problem

b)

When a computer is especially intelligent.

48.

Tiny little cells in our brain are

a)

Neurans

b)

Neurons

c)

Neurens

d)

Neuruns

49.

Algorithm

a)

The use of two or more processors, (cores, computers) in combination to solve a single problem.

b)

A step-by-step process to complete a task.

c)

Being correct and precise.

d)

Important to the matter at hand.

50.

This is a system of Programs and Data-Structures that mimics the operation of the human brain:

a)

a. Intelligent Network

b)

b. Decision Support System

c)

c. Neural Network

d)

d. Genetic Programming