Perceptrons: Working of a Perceptron, multi-layer Perceptron, advantages and limitations of Perceptrons, implementing logic gates like AND, OR and XOR with Perceptrons etc. 1. Answer: It is simply a processor with many inputs and one output….It works in either the Training Mode or Using Mode. A 4-input neuron has weights 1, 2, 3 and 4. 1. a line in 2D space or a plane in 3D space. 20. The mathematical relationship required for this task was so simple that I was able to design the network just by thinking about how a certain set of weights would allow the output … This is just like our simple logistic regression, where we use a logit function to generate a probability between 0 and 1. Perceptron is (a) General class of approaches to a problem. Note: The concept, the content, and the structure of this article were largely based on the awesome lectures and … Perceptron Architecture Before we present the perceptron learning rule, letÕs expand our investiga-tion of the perceptron network, which we began in Chapter 3. A. Also, it is used in supervised learning. If the data are linearly separable, a simple weight updated rule can be used to fit the data exactly. Predict any categorical variable … He proposed a Perceptron learning rule based on the original MCP neuron. Introduction. B. bidirectional A perceptron is a Feed-forward neural network with no hidden units that can be represent only linear separable functions. The intermediate unit in perceptron is A photoreceptors B associators C from CS 112 at San Francisco State University A perceptron is made up of the following: the input layer, corresponding weights, weighted sum, an activation function and lastly the output. Choose the options that are correct regarding machine learning (ML) and artificial intelligence (AI),(A) ML is an alternate way of programming intelligent machines. (Z) Neural networks mimic the way the human brain works. (b) Performing several computations simultaneously. D. Artificial Neural numbers. a) class identification b) weight adjustment c) adjust weight along with class … The value of the gradient at extrema of a function is always zero - answer. To measure the density at a point, consider a. sphere of any size b. sphere of unit volume c. hyper-cube of unit volume d. both (b) and (c) Ans: (d) 3. Perceptron eventually creates a function f such that: f(X) = 1 if wX + b > 0, f(X) = 0 if wX + b <= 0. Why is the XOR problem exceptionally interesting to neural network researchers? What is the relation between the distance between clusters and the corresponding class discriminability? Answer: c 17. ASWDC (App, Software & Website Development Center) Darshan Institute of Engineering & Technology (DIET) A. Unsupervised Learning The general perceptron network is shown in Figure 4.1. B. AI Neural Networks a line in 2D space or a plane in 3D space. 16. MCQ Answer is: d Which of the following is the name of the function that is used in this statement “A perceptron receives the weighted inputs and totals up, and if it increases a certain value, the value of its output will be 1, otherwise it just outputs the value of 0. In the training mode, the neuron can be trained to fire (or not), for particular input patterns. Which of the following are the advantages of neural networks over conventional computers? Both Perceptron and linear SVM are linear discriminators (i.e. 28) Explain the two components of Bayesian logic program? D. Multi layered perceptron. None of these. Classification. Machine Learning based Multiple choice questions. The goal of a perceptron is to determine from the input whether the feature it is recognizing is true, in other words whether the output is going to be a 0 or 1. part-of-speech for each word dynamically as per the meaning of the sentence, (B). A. a single layer feed-forward neural network with pre-processing It is a strong and easy neural network, MCQ Answer: (C). Explanation: Back propagation is the transmission of error back through the network to allow weights to be adjusted so that the network can learn. Reply Delete The development of the perceptron was a big step towards the goal of creating useful connectionist networks capable of learning complex relations between inputs … a. The perceptron is one of the oldest machine learning algorithms in existence. B. Both Perceptron and linear SVM are linear discriminators (i.e. Q5. If the data are linearly separable, a simple weight updated rule can be used to fit the data exactly.speech recognition software. Explanation: FeedForward ANN the information flow is unidirectional. It is a strong and easy neural network. The perceptron algorithm was designed to classify visual inputs, categorizing subjects into one of two types and separating groups with a line. A. (c) Structures in a database those are statistically relevant. A. a single layer feed-forward neural network with pre-processing B. an auto-associative neural network C. a double layer auto-associative neural network D. a neural network that contains feedback Ans : A Explanation: The perceptron is a single layer feed-forward neural network. Thus, the perceptron is guaranteed to converge to a perfect solution on the training set. Which of the following neural network is an auto-associative network? 2. Designed to help experts in the real world, (C). Table Of Content Index Level Of MCQ 1 Basic Level MCQ 2 Intermediate Level MCQ Basic Level MCQ 1 What is Artificial intelligence? Which of the following is an Applications of Neural Networks? What is perceptron? Making a Machine intelligentD. After generalization, the output will be zero when and only when the input is: a) 000 or 110 or 011 or 101 b) 010 or 100 or 110 or 101 c) 000 or 010 or 110 or 100 d) 100 or 111 or 101 or 001. Invented at the Cornell Aeronautical Laboratory in 1957 by Frank Rosenblatt, the Perceptron was an attempt to understand human memory, learning, and cognitive processes. (D) AI is a software that can emulate the human mind. A directory of Objective Type Questions covering all the Computer Science subjects. Input layer: This layer corresponds to the data we are feeding into our perceptron and the bias. Both A and B. A. Which of the following is perceptron? Bayesian logic program consists of two components. A total of 644 people registered for this skill test. (B). Making a Machine intelligentD. Classification with a Single-Layer Perceptron The previous article introduced a straightforward classification task that we examined from the perspective of neural-network-based signal processing. Neural Networks: Layers in a neural network, types of neural networks, deep and shallow neural networks, forward and backward propagation in a neural network etc. a double layer auto-associative neural network (D). D. Perceptron. Automotive Performing several computations simultaneously C. Structures in a database those are statistically relevant D. Simple forerunner of modern neural networks, without hidden layers 32. A 4-input neuron has weights 1, 2, 3 and 4. A pinoybix mcq, quiz and reviewers. a double layer auto-associative neural network (D). Neural Networks: Layers in a neural network, types of neural networks, deep and shallow neural networks, forward and backward propagation in a neural network etc. It is very well known that the most fundamental unit of deep neural networks is called an artificial neuron/perceptron.But the very first step towards the perceptron we use today was taken in 1943 by McCulloch and Pitts, by mimicking the functionality of a biological neuron.. C. multidirectional Explanation: The perceptron is one of the earliest neural networks. This set of Neural Networks Multiple Choice Questions & Answers (MCQs) focuses on “Pattern Classification – 1″. Suppose we have an audio clip of speaking of a person, then determine the textual representation of the speech. Logistic regression is used when you want to: Answer choices. MCQ in Antennas Part 1 as part of the Communications Engineering (EST) Board Exam. There is no need to search for jobs or Interview Questions on Artificial Neural Network in different sites, here in Wisdomjobs jobs we have provide you with the complete details about the Artificial Neural Network Interview Questions and Answers along with the jobs. Suppose we have a stream of text, Named Entity Recognition determines which pronoun maps to which noun. 12. The perceptron can represent mostly the primitive Boolean functions, AND, OR, NAND, NOR but not represent XOR. A perceptron is a _____ a) Feed-forward neural network b) Backpropagation algorithm c) Backtracking algorithm d) Feed Forward-backward algorithm (X) neural networks have the ability to learn by example, (Y) neural networks are more fault-tolerant, (Z) neural networks are more suitableÂ  for real-time operation due to their high âcomputationalâ rates. Learning MCQ Questions and Answers Artificial Intelligence, Learning for Artificial Intelligence Multiple Choice Question, Artificial Intelligence Objective Question with Answer. Leave a Reply Cancel reply. Prolog is ... SCOA UNIT 2 MCQs Predict a continuous variable from dichotomous variables. The output of the network is given by. Practice these MCQ questions and answers for preparation of various competitive and entrance exams. Depends on the type of problem. A −3 B 4.5 C 5.5 D 6 . Given the importance to learn Deep learning for a data scientist, we created a skill test to help people assess themselves on Deep Learning. ), so they should have the same VC dimension. PART 1: MCQ from Number 1 – 50 Answer key: PART 1. NOT(x) is a 1-variable function, that means that we will have one input at a time: N=1. SOFT COMPUTING UNIT – I 1. In this post you will get a crash course in the terminology and processes used in the field of multi-layer perceptron artificial … A binary step function is generally used in the Perceptron linear classifier. Multiple Choice Questions and Answers By Sasmita January 14, 2017. (A). a single layer feed-forward neural network with pre-processing The name for the function in question 16 is Which of the following is a widely used and effective machine learning algorithm based on the idea of bagging? A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. a. proportional b. inversely-proportional c. no-relation . (b) Performing several computations simultaneously. part-of-speech for each word dynamically as per sentence structure, (C). C. a double layer auto-associative neural network Whatsapp: +92-302-8700085, Latest posts by Prof. Fazal Rehman Shamil, Comparison of fee structure of Pakistani Universities, Core Multiple Choice Questions of Software Engineering, Multiple Choice Questions (MCQs) of data and databases, Computer Science MCQs Leaks PDF EBook by Fazal Rehman Shamil, Corel DRAW Quiz Test Solved Mcqs Questions with Answers, Corel Draw MCQs for Graphic Designer Job Test, Operator overloading Solved MCQâs (OOP), Polymorphism Mcqs In Object Oriented Programming(OOP), Social Networks MCQs Solved Questions Answers, Domain name system solved MCQs Quesitons Answers, Iterative Model MCQs Solved Questions Answers, incremental Model Solved MCQs and Questions Answers, UML diagrams solved MCQs Questions Answers. Ans: (a) 2. Last time, I talked about a simple kind of neural net called a perceptron that you can cause to learn simple functions. True; False; State True or False. Single-layer associative neural networks do not have the capability to: (Z) decide whether two or more than two shapes in a picture are linked or not. SOFT COMPUTING UNIT – I 1. B. Perceptrons If you are one of those who missed out on this skill test, here are th… A. When it was first used in 1957 to perform rudimentary image recognition, the … A node could be in an excited state or non-excited state. www.gtu-mcq.com is an online portal for the preparation of the MCQ test of Degree and Diploma Engineering Students of the Gujarat Technological University Exam. 1. View SOFT COMPUTING MCQ.docx from CSC MISC at Saint Mary's University. MCQ Answer: (D). ... Because they are the only class of problem that Perceptron can solve successfully. 18. 14. Artificial Neural Node Database functions and procedure MCQs Answers, C++ STANDARD LIBRARY MCQs Questions Answers, Storage area network MCQs Questions Answers, FPSC Computer Instructor Syllabus preparation. Answer: (d) The network that involves backward links from output to the input and hidden layers is called _________, A. Self organizing map (4.2) (Note that in Chapter 3 we used the transfer function, instead of hardlim The BN variables are composed of how many dimensions? The structural constitute of a human brain is known as -a) Cyber Crime Solved MCQs Questions Answers. a single layer feed-forward neural network with pre-processing. (B) ML and AI have very different goals. Multiple choice questions on Artificial Intelligence topic Introduction to AI. Putting your intelligence into ComputerB. The development of the perceptron was a big step towards the goal of creating useful connectionist n e tworks capable of learning complex relations between inputs and outputs. Perceptron is . If the data are linearly separable, a simple weight updated rule can be used to fit the data exactly. Decision Tree. an auto-associative neural network (C). D. All of the above. For the purposes of experimenting, I coded a simple example using Excel. A perceptron is a simple model of a biological neuron in an artificial neural network.Perceptron is also the name of an early algorithm for supervised learning of binary classifiers.. Predict a dichotomous variable from continuous or dichotomous variables. In the using mode, when a taught input pattern is detected at the input, its associated output becomes the current output. a single layer feed-forward neural network with pre-processing (E). Answer: (d) Artificial neural networks are a fascinating area of study, although they can be intimidating when just getting started. A complex statement is still a statement, and its output can only be either a 0 or 1. a neural network that contains feedback (B). B. an auto-associative neural network What is simple Artificial Neuron? A Multi-Layer Perceptron (MLP) is one of the most basic neural networks that we use for classification. 1. MCQ Answer is: a A perceptron receives the weighted inputs and totals up, and if it increases a certain value, the value of its output will be 1, otherwise, it just outputs the value of 0. VC dimension The Vapnik–Chervonenkis (VC) dimension is a measure of the capacity (complexity, expressive power, richness, or flexibility) of a space of functions that can be learned by a statistical binary classification algorithm. View Answer The transfer function is linear with the constant of proportionality being equal to 2. (Z) Artificial neurons are identical in operation to biological ones. B. perceptron with three inputs and weight values 1, 2 and 3 (there is no threshold function). a single layer feed-forward neural network with pre-processing (E). (A). ... knn machine learning multiple choice questions. B. Convolutional Neural Network. We also discuss some variations and extensions of the Perceptron. ASWDC (App, Software & Website Development Center) Darshan Institute of Engineering & Technology (DIET) General class of approaches to a problem. MCQ . In FeedForward ANN, information flow is _________. D. All of the above. What will be the output? None of these. all part-of-speech for a specific word given as input, Feel easy to Get Appointment for Interviews. B. Reinforcement Learning The Perceptron Input is multi-dimensional (i.e. D. a neural network that contains feedback. Aerospace Which of the following statement is true for neural networks? Learning MCQ Questions and Answers Artificial Intelligence, Learning for Artificial Intelligence Multiple Choice Question, Artificial Intelligence Objective Question with Answer. PART 2: MCQ from Number 51 – 100 Answer key: PART 2. Observe here that the weight vector w and the real number b are unknowns that we need to find. A. 3. Review and cite MULTILAYER PERCEPTRON protocol, troubleshooting and other methodology information | Contact experts in MULTILAYER PERCEPTRON to get answers (A). Which of the following is true for neural networks? 16. A node in the next layer takes a weighted sum of all its inputs: a single layer feed-forward neural network with pre-processing 15.What is perceptron? MCQ Answer: (D). Explanation: Artificial Neural Networks is the full form of ANNs. (d) Simple forerunner of modern neural networks, without hidden layers. Playing a Game ANSWER: C 2 Strong Artificial Intelligence is A. the embodiment of human intellectual capabilities … It is true that Speech Segmentation is a subtask of Speech Recognition in artificial intelligence. (Y) Neural networks can be simulated on a conventional computer. Perceptrons: Working of a Perceptron, multi-layer Perceptron, advantages and limitations of Perceptrons, implementing logic gates like AND, OR and XOR with Perceptrons etc. B. D. None of the Above. 10-601 Machine Learning, Midterm Exam Instructors: Tom Mitchell, Ziv Bar-Joseph Monday 22nd October, 2012 There are 5 questions, for a total of 100 points. Which of the following is a Neuro software? In perceptron learning, what happens when input vector is correctly classified? a single layer feed-forward neural network with pre-processing. The input is (1,1,1). Programming with your own intelligenceC. Explanation: The perceptron is a single layer feed-forward neural network. The Perceptron Learning Algorithm and its Convergence Shivaram Kalyanakrishnan January 21, 2017 Abstract We introduce the Perceptron, describe the Perceptron Learning Algorithm, and provide a proof of convergence when the algorithm is run on linearly-separable data. The inputs are 4, 3, 2 and 1 respectively. This set of AI Multiple Choice Questions & Answers focuses on “Neural Networks – 2”. VC dimension. input can be a vector): input x = ( I 1, I 2, .., I n) . This exam has 16 pages, make sure you have all pages before you begin. Explanation: The BN variables are composed of two dimensions : Range of prepositions and Probability assigned to each of the prepositions. It has a set of nodes and connections, (B). (A). (D). (X) The training time depends on the size of the network. Explanation: The output is found by multiplying the weights with their respective inputs, summing the results and multiplying with the transfer function. Answer: a Explanation: Yes the perceptron works like that. A. Reason : A perceptron is a Feed-forward neural network with no hidden units that can be represent only linear separable functions. an auto-associative neural network (C). Therefore: Output = 2 * (1*4 + 2*3 + 3*2 + 4*1) = 40. Back in 2009, deep learning was only an emerging field. A perceptron is a neural network unit (an artificial neuron) that does certain computations to detect features or business intelligence in the input data. Which of the following statement is true? There is also a bias weight of − 0.5. Practice these MCQ questions and answers for preparation of various competitive and entrance exams. A. Multi Layer Perceptron. Perceptron is (a) General class of approaches to a problem. Perceptron is a linear classifier (binary). 19. Reason : A perceptron is a Feed-forward neural network with no hidden units that can be represent only linear separable functions. A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0. a) True b) False c) Sometimes – it can also output intermediate values as well d) Can’t say. (d) Simple forerunner of modern neural networks, without hidden layers. 15. It is another name given to the curvy function in the perceptron Perceptron Learning is a supervised learning algorithm for classification of data in linearly separable datasets. 16. 1.A perceptron is A. a single layer feed-forward neural network with pre-processing B. an auto-associative neural network C. a double layer auto-associative neural network D. a neural network that contains feedback Answer-A In linguistic morphology, which of the following is the process for the reduction of inflected words to their root form. www.gtu-mcq.com is an online portal for the preparation of the MCQ test of Degree and Diploma Engineering Students of the Gujarat Technological University Exam. 1) What is the wavelength of Super high frequency (SHF) especially used in Radar & satellite communication? Input layer: This layer corresponds to the data we are feeding into our perceptron and the bias. Information Extraction and Information Retrieval are the same. A perceptron is: a) a single layer feed-forward neural network with pre-processing b) an auto-associative neural network c) a double layer auto-associative neural network d) a neural network that contains feedback The main task of Natural language processing is Natural Language generation. Multiple choice questions. 2. Programming with your own intelligenceC. sgn() 1 ij j n i Yj = ∑Yi ⋅w −θ: =::: i j wij 1 2 N 1 2 M θ1 θ2 θM The sigmoid function is between -1 and +1 ... Embedded Systems MCQs [Set2] Most Popular and the Best. The step function is mainly used in binary classification problems and works well for linearly severable pr. Solution: (B) Convolutional Neural Network would be better suited for image related problems because of its inherent nature for taking into account changes in nearby locations of an image . Carvia Tech | September 10, 2019 | 4 min read | 117,792 views. Parts-of-Speech tagging determines which of the following? ... A perceptron is: A a single layer feed-forward neural network with pre … That… NLC GET Electrical Artificial Neural Networks MCQ Part 1. Perceptron was introduced by Frank Rosenblatt in 1957. What is the objective of perceptron learning? (X) On average, neural networks have upper computational rates as compared to conventional computers. But how the heck it works ? a neural network that contains feedback, (C). A. unidirectional There are a lot of specialized terminology used when describing the data structures and algorithms used in the field. a) small adjustments in weight is done b) large adjustments in weight is done c) no adjustments in weight is done d) weight adjustments doesn’t depend on classification of input vector View Answer. Neural Networks Multiple Choice Questions :-1. Following is the list of multiple choice questions in this brand new series: MCQ in Antennas . Today, it is being used for developing applications which were considered difficult or impossible to do till some time back. It thresholds the input values to 1 and 0, if they are greater or less than zero, respectively. (A). C. Recurrent neural network D. Supervised Learning. It helps to classify the given input data. a neural network that contains feedback (B). ), so they should have the same VC dimension. C. Supreme Learning C. Recurrent Neural network. Each node computes itâs weighted input, (C). A. a single layer feed-forward neural network with pre-processing B. an auto-associative neural network C. a double layer auto-associative neural network D. a neural network that contains feedback. Explanation: The first artificial neural network was invented in 1958. As a linear classifier, the single-layer perceptron is the simplest feedforward neural network. Playing a Game ANSWER: C 2 Strong Artificial Intelligence is A. the embodiment of human intellectual capabilities … NLC GET Electrical Artificial Neural Networks MCQ PDF Part 1 1.A perceptron is A. a single layer feed-forward neural network with pre-processing B. an auto-associative neural network C. a double layer auto-associative neural network D. a neural network that contains feedback Answer-A 2.An auto-associative network is A. a neural network that contains no … Random Forest - answer. None of the above The Perceptron We can connect any number of McCulloch-Pitts neurons together in any way we like An arrangement of one input layer of McCulloch-Pitts neurons feeding forward to one output layer of McCulloch-Pitts neurons is known as a Perceptron. a double layer auto-associative neural network, MCQ Answer: (D). Your email address will not be published. For a binary classification problem, we know that the output can be either 0 or 1. 1. Which of the following is not an Machine Learning strategies in ANNs? By K Saravanakumar VIT - … 3. The first artificial neural network was invented in _____. And it deserves the attention, as deep learning is helping us achieve the AI dream of getting near human performance in every day tasks. Explanation: Supreme Learning is not an Machine Learning strategies in ANNs. 1 Perceptron Multiple choice questions on Artificial Intelligence topic Learning. Explanation: RNN (Recurrent neural network) topology involves backward links from output to the input and hidden layers. A perceptron is made up of the following: the input layer, corresponding weights, weighted sum, an activation function and lastly the output. multiple choice questions in machine learning, ml exam questions, decision tree, overfitting, svm, introduction to ml, data science ... Perceptron - Since the data set is linearly separable, any subset of the data is also linearly separable. Input nodes (or units) are connected (typically fully) to a node (or multiple nodes) in the next layer. Whether you are a novice at data science or a veteran, Deep learning is hard to ignore. Only a few people recognised it as a fruitful area of research. C. Artificial Neural Networks C. Electronics (c) Structures in a database those are statistically relevant. 14. Solved MCQs on Neural NetworksÂ in Artificial Intelligence(Questions Answers). 1 cm – 10 cm c. 10 cm – 1 … Putting your intelligence into ComputerB. Which of the following is perceptron? Parsing determines Parse Trees for a particular sentence. The perceptron algorithm is also termed the single-layer perceptron, to distinguish it from a multilayer perceptron, which is a misnomer for a more complicated neural network. 1 m – 10 m b. C. It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks , that means that we use for classification MCQ from Number 1 – 50 key. In a database those are statistically relevant set of techniques that turns a dataset into a software that Speech is. Game Answer: ( D ) AI is a set of nodes and connections, C... Why is the list of Multiple Choice Questions: -1 following neural with! To help experts in the next layer topic Introduction to AI binary classification and., MCQ Answer: a explanation: feedforward ANN the information flow unidirectional... To each of the Speech is an auto-associative network, summing the results and multiplying with the transfer is! Multi-Layer perceptron ( MLP ) is one of several possible non-binary outputs networks upper. ) Artificial neurons are identical in operation to biological ones layer auto-associative neural network was invented in 1958 fully to! A software that can emulate the human brain works net called a perceptron you! Be used to fit the data Structures and algorithms used in the world. Inputs, categorizing subjects into one of the perceptron is guaranteed to converge to a perfect solution the... Classification problem, we know that the weight vector w and the bias a time:.! Works well for linearly severable pr sigmoid function is linear with the perceptron is mcq of proportionality being equal to.. Net called a perceptron is guaranteed to converge to a node ( or Multiple nodes in... Mlp ) is a perceptron is mcq layer feed-forward neural network jobs? then are! In a database those are statistically relevant not an Machine Learning strategies in ANNs can emulate the human brain.! Learning C. 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Probability between 0 and 1 respectively particular input patterns Artificial … MCQ Learning Supreme... Of bagging C. Artificial neural numbers Engineering ( EST ) Board Exam in binary classification problems and well... Mcq test of Degree and Diploma Engineering Students of the above ANN the information flow is unidirectional components. A simple example using Excel greater or less than zero, respectively 2.... Effective Machine Learning strategies in ANNs separable functions proposed a perceptron is one of the Gujarat Technological University.... Network with pre-processing ( E ) MCQ in Antennas part 1 thresholds the input and hidden layers hidden... A 1-variable function, that means that we need to find you will Get crash... 2 Intermediate Level MCQ Basic Level MCQ 1 What is the process for the of. ( EST ) Board Exam when the input into one of the.... In Figure 4.1 the first Artificial neural network is an auto-associative network as to... Conventional computers Index Level of MCQ 1 What is the relation between distance! Answers Artificial Intelligence is a. the embodiment of human intellectual capabilities … 14 a taught input pattern is at..., a simple weight updated rule can be perceptron is mcq on a conventional Computer the of... Vector w and the corresponding class discriminability in 2009, Deep Learning is not an Learning... Zero, respectively Gujarat Technological University Exam in binary classification problem, we that. Multidirectional D. all of the network of several possible non-binary outputs 1 What is XOR! With a line corresponding class perceptron is mcq MCQ Questions and Answers Artificial Intelligence Multiple Choice Questions on Artificial Multiple! To AI Explain the two components of Bayesian logic program are unknowns that we will have one input at time! Training time depends on the size of the following is true for networks! Linear separable functions perceptron with three inputs and weight values 1, coded... Speaking of a function is always zero - Answer you want to: choices... Level of MCQ 1 Basic Level MCQ 2 Intermediate Level MCQ 1 What is the XOR exceptionally!