The neural network given below takes two binary valued inputs x1,x2 e{0, 1} and the activation function is the binary threshold function (h(x)=l if x>0;0 otherwise). The OR logical functions does it compute +1 -30 20 he(x) 20

Q: The neural network given below takes two binary valued inputs x1,x2 ϵ{0, 1} and the activation…

A: The output H(x) is calculated as H(x) = 20*x1 + 20*x2 - 30

Q: Apply the backpropagation algorithm to the neural network given below. Find the weights after the…

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Q: Calculate the output of the neural network illustrated below using the following activation…

A: ANSWER:-

Q: Please design a neural network with one input layer, two hidden layers and one output layer. it has…

A: The Answer is

Q: Using linear activation function find out the output value(y) of the below listed neural network of…

A: The solution as per the given information

Q: Using linear activation function find out the output value(y) of the below listed neural network of…

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Q: Using linear activation function find out the output value(y) of the below listed neural network of…

A: Given:

Q: Using linear activation function find out the output value(y) of the below listed neural network of…

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Q: Calculate the output of the neural network illustrated below using the following activation…

A:

Q: Draw a neural network (including structure, weights and thresholds) that computes the majority…

A: Solution  #Use python to build a neural network: import numpy, random, os#package learnr = 1…

Q: Find the dimensions and outputs of the expressions w1,w2,w3,b1,b2,b3 in the given neural network a…

A: Given : Neural network with whole architecture. Task : Dimensions of w1,w2,w3,b1,b2,b3

Q: The weights, activation function, and set of input values for a Neural Network are given below:…

A: Given Data :      S1 S2 S3 x1 2 4 1 x2 3      2 3 x3 3 6 -2…

Q: In artificial neural networks we use activation functions. Explain why you would select on…

A: In artificial neural networks, a node activation function defines the output of the set input or…

Q: In artificial neural networks we use activation functions. Explain why you would select on…

A: Activation Function is a type of function that is  added in the artificial neural network to help…

Q: A. A neural network that represent AND logic gate is shown in the figure. Train the neural network…

A: Given that: - The given network represent the AND gate and this can be represented as: - x1…

Q: The simplest neural network is a(n) _____________________________

A: Here have to determine about simplest neural network.

Q: By using neural network algorithm solve the XOR problem. Where X1 and X2 are inputs Y is the output.…

A: Answer : import numpy as np   X = np.array(([0, 0], [0, 1], [1, 0],[1,1]), dtype=int)   # X and Y…

Q: 2. Neural Networks Apply the back-propagation algorithm to the following network. Your training…

A: g = in^2 g’ = 2 * in To answer this question, I will normalize my inputs. I1 and I2 will become 0.25…

Q: Question# 01: Consider the simple neural network below: 0.1 Input A = 0.1 0.2 0.5 Output 0.3 Input…

A: Assume that neurons have a sigmoidal activation function ,Target value is 1 and learning rate is…

Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

A: Given figure, Y= W1 X1 + W2 X2 + W3 X3 + W4 X4 + W5 X5

Q: Why is a sigmoid function useful as an activation function for a neural network that is being…

A: The problem is based on the neural networks in artificial intelligence.

Q: The following Boolean function: f(x1, x2, x3) = 1 if and only if exactly one of x1, x2 and x3 is 1.…

A: Given: function: f(x1, x2, x3) = 1 if and only if exactly one of x1, x2 and x3 is 1. Now what's our…

Q: Choose the best answer A perceptron is: a single layer feed-forward neural network with…

A: A perceptron is a single-layer neural network. Perceptron is a linear classifier (binary). Also, it…

Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

A: Solution as per the given information

Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

A: The solution as per the given information

Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

A: Given: -   The solution as per the given information

Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

A: Given: -   Solution as per the given information

Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

A: The solution as per the given information

Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

A: Solution as per the given information

Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: Machine Learning Lab: Using linear activation function find out the output value(y) of the below…

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Q: “Convolutional Neural Networks can carry out various forms of transformation (rotations or scaling)…

A: Convolutional Neural Networks: In the straightforward kind it's additionally called KNN. A…

Q: Training neural networks has the potential problem of overfitting the training data. Select one:…

A: The problem is based on the basics of Neural Networks in Deep Learning.

Q: Please wrrite the code to train the neural network using back propagation algorithm for XOR problem.…

A: Program Approach: Importing the requisite Python libraries. Define the Sigmoid Function and…

Q: Which one of the following has best interpretability O Neural Networks Ensemble Tree Decision Tree O…

A: Answer: The right choice is option C. Decision Tree. The explanation is in step 2.

Q: Given PEAS of part-picking robot, give the environment types (fully observable vs partially…

A: Specialist or Agent Environment in AI  :- A climate is everything on the planet which encompasses…

Q: Q2:- The bitmap shown in Figure 1 is designed to display all numbers from 0--9 and all letters…

A: I have answered this question in step 2.

Q: For the task of object recognition from images, why is convolutional neural network more favourable…

A: A convolutional neural network is more favourable than multilayer perception neural network because:…

Q: E2.2 Consider a single-input neuron with a bias. We would like the output to be -1 for inputs less…

A: Answer : 1). The transfer function that is required would be a Hard Limit function f(n) whose…

Q: E2.2 Consider a single-input neuron with a bias. We would like the output to be -1 for inputs less…

A: Answer : 1). The transfer function that is required would be a Hard Limit function f(n) whose…

Q: E2.2 Consider a single-input neuron with a bias. We would like the output to be -1 for inputs less…

A: Answer : 1). The transfer function that is required would be a Hard Limit function f(n) whose…

Q: E2.2 Consider a single-input neuron with a bias. We would like the output to be -1 for inputs less…

A: (i ) The transfer function that is required would be a Hard Limit function f(n) whose restrictions…