Neural Networks
Q.1- What do you understand by Artificial Neural Networks(ANNs)?
Ans. An ANN is a computational network based on biological neural networks that
construct the structure of human brain.
Q.2- Define (i) Deep Learning (ii) Machine Learning.
Ans. (i) In Deep learning the machine is trained with huge amount of data which helps it to
train itself around the data.
(ii) Machine learning enables machines to improve at tasks with experience
Q.3- What is the key advantage of neural network?
Ans. Neural Network- able to extract data features automatically without needing the input of the programmer.
Q.4- A neural network is a machine learning algorithm based on the model of a human neuron.
(i) True
(ii) False
Ans. (i) True
Q.5- Define any Two (i) Input Layer (ii) Hidden Layer (iii) Output Layer
Ans. Role of Input Layer- acquire date and feed it to neural network Role of Hidden Layers- Whole processing occurs in hidden layers
Role of Output Layer – Accepts final processed data from hidden layer.
Q.6- Which approach is commonly used when we have a known dataset or labeled dataset?
a) Supervised b) unsupervised c) Rule based d) Learning based
Ans. c) Rule based
Q.7- Which approach is commonly used when the data is unknown/random or unlabeled?
a) Supervised b) unsupervised c) Rule based d) Learning based
Ans. d) Learning based
Q.8- Which learning involves training the machine using data?
a) Supervised b) unsupervised c) Rule based d) Learning based
Ans. a) Supervised
Q.9- in which learning machine is restricted to find the hidden structure in unlabeled data
by itself
a) Supervised b) unsupervised c) Rule based d) Learning based
Ans. b) unsupervised
Q.10- which learning is also known as machine learning method
Ans. a) Supervised b) unsupervised c) Reinforcement d) Classification
Q.11- Write the full form of the following organizations.
i. ANN ii. BNN
Ans. Ans : 1. ANN Artificial Neural Network
2. BNN Biological Neural Network
Q.12- Define the following terms
i. Deep Learning
ii. Neural Network
Ans. i) Deep Learning : It is an Artificial Intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making.
It is a subset of machine learning which helps the machine to take decisions and learn from large datasets
ii) Neural Network : A neural network is defined as a combination of algorithms to understand the relationship between various sets of data to process and then takes out some meaningful information from it.
Q.13- What is the need of neural networks in Artificial Intelligence?
Ans. They are used to solve real-life complex problems. These networks can learn and create the relationships between all the inputs and gives the result. They can handle non linear and complex problems very effectively. The main advantage of neural networks is that they are able to extract data features automatically without needing any input from the programmer.
Q.14- Sketch2Code is a Microsoft web-based solution to transform any handmade designs into HTML code using Artificial Intelligence. 1
i. True
ii. False
Ans. : True
Q.15- What are the three methods or techniques used for identifying, processing and classifying data in deep learning systems?
Ans. Multi-Layer Perceptrons (MLP)
Convolutional Neural Networks (CNN)
Recurrent Neural Networks (RNN)
Q.16- What is Artificial Neural Network?
Ans. The term "Artificial Neural Network" is derived from Biological neural networks that develop the structure of a human brain. Similar to the human brain that has neurons interconnected to one another, artificial neural networks also have neurons that are interconnected to one another in various layers of the networks.
Q.17- ANNs are made up of .............................. nodes which imitate biological neurons of the human brain.
Ans. Input Nodes.
Q.18- In general, a neural network consists of an input and output layer with one or multiple________ layers within..
Ans. Hidden Layer.
Q.19- Write any two similarities between Biological Neural Networks and Artificial Neural Networks.
Ans. 1. The presence of neurons as the most basic unit of the nervous system.
2. The input is directly passed to a neuron and output is also directly taken from the neuron,
Q.20- Write any two advantages of Artificial Neural Network?
Ans. 1. A neural network can implement tasks that a linear program cannot.
2. A neural network determines and does not require to be reprogrammed.
Q.21- Write any 3 Attributes of Artificial Neural Networks.
Ans. 1. Faster in processing information. Response time is in nanoseconds.
2. Serial processing.
3. Less size & complexity. It does not perform complex pattern recognition tasks.
Q.22- Write any 3 Applications of Artificial Neural Networks.
Ans. 1. Facial Recognition.
2. Stock Market Prediction.
3. Social Media.
4. Aerospace.
5. Defence.
Q.23- Neural Network is an instance of deep learning technology.
True/False
Ans. True
Q.24- Explain the difference between Neural networks and Conventional computing.
Ans. Neural Network-More Probabilistic, No Central Processor, Respond in parallel
Conventional Computing- works on serial processing logic, Computational steps are deterministic, sequential and logical, Uses Central Processor.
Or
Conventional computers have to learn by rules, while artificial neural networks learn by example, by doing something and then learning from it.
Q.25- What is need of neural network in artificial intelligence ?
Ans. They are used to solve real-life complex problems. These networks can learn and create the relationships between all the inputs and gives the result. They can handle non linear and complex problems very effectively. The main advantage of neural networks is that they are able to extract data features automatically without needing any input from the programmer.
