The use of a single Sigmoid/Logistic neuron in the output layer is the mainstay of a binary classification neural network. This is because the output of a Sigmoid/Logistic function can be conveniently interpreted as the estimated probability(p̂, pronounced p-hat) that the given input belongs to the “positive” class. https://www.incegna.com/post/binary-classification-neural-networks Check our Info : www.incegna.com Reg Link for Programs : http://www.incegna.com/contact-us Follow us on Facebook : www.facebook.com/INCEGNA/? Follow us on Instagram : https://www.instagram.com/_incegna/ For Queries : [email protected] #deeplearning,#binaryclassification,#neuralnetworks,#Sigmoid,#Logisticneuron,#linearnode,#sigmoidnode,#artificialneuralnetwork,#visualization,#datasets,#dependentvector,#keras,#tensorflow,#numpy,#pandas,#python https://www.instagram.com/p/B9n0PDcAhlK/?igshid=1p6dvf2n89j9h
