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a) i. A perceptron is a learning algorithm used for linear classification; it can be interpreted geometrically as an intersecting hyperplane, or algebraically as a classification function over a dot product.So, in essence, perceptrons can only solve linearly separable problems. A;gebraically, a non linearly separable problem would require from a perceptron to learn conflicting weights (say, the line -0.2x-y<0 is to be classified as Men, though not for all...

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