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Category Archives: Neural Networks
sigmoid function fail
I thought this would be one of the easier things I had set out to do tonight. But does that look like a sigmoid function to you? Time for bed. [Update: Fixed. I am clueless with matplotlib. Need to learn. … Continue reading
Posted in Coding, Neural Networks
Tagged backpropagation, fail, matplotlib, neural network, python, sigmoid
1 Comment
Predicting Gambling behavior
“Using Neural Networks to Model the Behavior and Decisions of Gamblers, in Particular, Cyber-Gamblers.” by Victor K. Y. Chan. A system is written that utilizes a back-propagation neural network to model Texas Holdem gamblers’ behavior, based on data collected from a cyber gambling … Continue reading
Posted in Algorithm, Emergence, Neural Networks
Tagged backpropagation, neural network, poker, prediction, publication
1 Comment
Le Cun and Backpropagation
A couple of posts ago I wrote about an interview with Yann Le Cun. I subsequently found this interesting note in Smith’s Neural Networks for Statistical Modeling: “Backpropagation is an example of multiple invention. David Parker (1982,1985) and Yann LeCun … Continue reading
Explanation of "multi-layer backpropagation Neural network called a Convolution Neural Network"
In my last post I said: The technology behind the ATMs was developed by LeCun and others almost 10 years ago, at AT&T Bell Labs… The algorithm they developed goes under the name LeNet, and is a multi-layer backpropagation Neural … Continue reading
Posted in Neural Networks
Tagged AT&T Bell Labs, backpropagation, CNN, Convolution Neural Network, definition, neural network, visual processing
1 Comment
Yann Le Cun
Yann Le Cun was recently featured on NYAS’s Science and the City podcast. He spoke about visual processing using Artificial Neural Networks (ANNs) and in particular his work on the system that reads the amounts on your cheques at the … Continue reading
