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WorksheetsNEURAL NETWORK
Total questions: 57
Worksheet time: 29mins
_________ type of model, the algorithm learns from a dataset which is labelled, and the algorithm uses the answer keys to evaluate its accuracy on the training data.
Supervised learning
UnSupervised learning
Reinforcement learning
In this type of model, the algorithms work towards accomplishing the goal or try to improve the performance in a particular task. This is used in gaming.
Reinforcement learning
Supervised Learning
UnSupervised Learning
•In this type of model, the algorithm learns and makes sense by extracting features/patterns from the unlabelled dataset provided (The system will evaluate by itself)
Unsupervised learning
supervised learning
Reinforcement learning
Information flows from
Input layer -> Hidden Layer-> Output layer
Feedforward Network
Backpropagation
Every Artificial Neural must have at least ______
two layers.
three layers.
four layers.
The neurons in the human brain regularly change their threshold.
True
False
The current Artificial Neural Networks are part of _____.
Weak Al systems.
Strong Al systems.
Future Al systems.
How many output layers are required for constructing an Artificial Neural Network?
1
3
2
Backpropagation calculates the ____ and propagates it back to earlier layers.
value
error
data
A neural network trained with labelled data is an example of . . .
supervised learning
unsupervised learning
In the neural network shown,
each neuron is connected to a random selection of other neurons in the network
every neuron is connected to every other neuron in the network
every neuron is conected to every neuron in the next layer
each neuron is connected to a random selection of neurons in the next layer
The activation of each neuron in a layer is determined by the __________ of the activations of all the neurons in the previous layer.
weighted sum
sum
level
What is this?
artificial intelligence
algorithm
neural network
How many hidden layers have the following Neural network
4
5
6
7
How many output layers have the following Neural network?
1
2
3
4
What is ANN
Artificial Neural Node
Artificial Neuro Nest
Artificial Neural Network
Artificial Neuron Naive
The most common Neural networks consist of three network layers: input layer, output layer and .............
neuron layer
hidden layer
algorithm layer
The most common Neural networks consist of three network layers: input layer, output layer and .............
neuron layer
hidden layer
algorithm layer
The input data travels over the network (propagates) until it reaches the output layer. This is called........
Back propagation
Forward propagation
This is where we insert the initial data for the neural network.
Input
Hidden Layer
Output
Which of the following is the feature of a neural network?
Extract information without any programming
All of these
Learn itself and produced the trained data
Provide the filtered information without input
The actual processing occurs in which of the following layer?
input layers
hidden layers
output layers
None of these
Reinforcement learning relies on output-related information.
True
False
In which of the following type of learning networks are trained to provide the correct output using several example units?
Supervised learning
Unsupervised learning
Reinforcement learning
All of these
In _________ learning only inputs provided but no output related data.
Supervised
Reinforcement
Un supervised
Semi-Supervised
Information flows from
Input layer -> Hidden Layer-> Output layer
Feedforward Network
Backpropagation
Every Artificial Neural must have at least ______
two layers.
three layers.
four layers.
The neurons in the human brain regularly change their threshold.
True
False
Neural network is inspired by .......
Human heart
Human lungs
Human brain
human eyes
Neural Network is type of ........... which is type of machine learning
natural language processing
deep learning
speech
robotics
What is this?
artificial intelligence
algorithm
neural network
The most common Neural networks consist of three network layers: input layer, output layer and .............
neuron layer
hidden layer
algorithm layer
This is where we insert the initial data for the neural network.
Input
Hidden Layer
Output
1) It is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings
Automated computations
IOT
Artificial Intelligence
None of these
(a) is a domain of AI related to data systems and processes, in which the system collects numerous data, maintains data sets and derives meaning/sense out of
them.
It is a subset of Artificial Intelligence which enables machines to improve at tasks with experience (data).
Machine Learning
AI
Deep Learning
In this model, the machine is trained with huge amounts of data which helps it in training itself around the data. Such machines are intelligent enough to develop algorithms for themselves.
AI
ML
DL
Domain of the game Rock Paper Scissors is
NLP
Data Science
Computer Vision
Domain of the AI used by price comparison websites is
Data Science
NLP
CV
The __________ helps us to summarise all the key points of Problem Scoping.
Problem Statement Template
4 Ws Problem canvas
Data Features
Identify the correct order of the 4Ws problem canvas.
Who? Why? When? Where?
Who? What? Where? Why?
Why? What? Where Who?
Why? What? Who? Where?
Under this block, you also gather evidence to prove that the problem you have selected actually exists. Identify the block of 4W problem canvas.
Who
what
where
why
The AI domain which can be used to predict AIR quality index is
NLP
CV
Data Science
Which of the following is not an AI application?
Google Maps
Writing suggestion in gmail
Face Recognition
Kahoot
4Ws Problem Canvas _______________________.
make many lives better and help our country achieve these goals.
helps in evaluating the solution related to the problem
helps in identifying the key elements related to the problem.
All of these
computational model inspired by the structure and functions of the biological neural network
artificial neural network (ANN)
neuron
weight
bias
collection of 'neurons' operating together at a specific depth within a neural network
Bias
Weight
Neuron
Layers
How many images would you need of a cat, for example, to train a neural network ?
about 10
a few hundred
one image
thousands
This is where we insert the initial data for the neural network.
Input
Hidden Layer
Output
Which is the correct structure of a Neural Network?
Output, Hidden Layer, Input
Hidden Layer, Input, Output
Input, Hidden Layer, Output
Which one of these is not an area of AI?
computer vision/image recognition
voice recognition
web design
robotics
This is a system of Programs and Data Structures that mimics the operation of the human brain :
Intelligent Network
Decision Support System
Neural Network
Genetic Programming
