Linear neurons - PowerPoint PPT Presentation

Terminology

Terminology. Usually, we draw neural networks in such a way that the input enters at the bottom and the output is generated at the top. Arrows indicate the direction of data flow. The first layer, termed input layer , just contains the input vector and does not perform any computations.

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CS344: Introduction to Artificial Intelligence (associated lab: CS386)

CS344: Introduction to Artificial Intelligence (associated lab: CS386). Pushpak Bhattacharyya CSE Dept., IIT Bombay Lecture 20 : Backpropagation 16 th Feb, 2012. Feedforward Network. Example - XOR. = 0.5. w 1 =1. w 2 =1. x 1 x 2. 1. 1. x 1 x 2. 1.5. -1. -1. 1.5. x 2. x 1.

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Lecture 9 MLP (I): Feed-forward Model

Lecture 9 MLP (I): Feed-forward Model. Outline. Multi-Layer Perceptron Structure Feed Forward Model XOR Example MLP Applications. Multi-Layer Perceptron Structure. A Three Layer Feed-forward Multi-Layer Perceptron. Two Layer Perceptron XOR Gate. Decision Boundaries of XOR.

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