Day #51 - Neural Networks

Happy New Year 2017. This post is on Neural Networks.

Neural Networks

• ANN - inspired by biological networks, Modelling network based on neurons
• Key layers - Input Layer, Hidden Layer, Output Layer
• Neural networks that can learn - Perceptrons, backpropagation networks, Boltzaman machines,recurrent networks
• In below example for XOR implementation we use backpropagation 

Implementation overview

• Initialize the edge weights at random (we do not exact weights we chose randomly, By training we find exact values)
• Calculate the error - we have some training data and some results - Supervised learning, Calculated output not logical output, Error term present 
• Calculate the changes of edge weights and update the weights (backpropagation process), Calculate edge weight changes and update accordingly
• Algorithm terminates when error rate is small

Simple Neural Network

Happy Pongal & Happy Learning!!!