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Perceptron
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211	Random Kernel Perceptron on ATTiny2313 Microcontroller Nemanja Djuric, Slobodan Vucetic Department of Computer and Information Sciences Temple University Add to Reading List Source URL: astro.temple.edu Language: English - Date: 2013-03-28 14:53:56 Computing Computer architecture Linux kernel Quantization Kernel Architecture of Windows NT Neural networks Software Perceptron
212	TRAIN AND ANALYZE NEURAL NETWORKS TO FIT YOUR DATA TRAIN AND ANALYZE NEURAL NETWORKS TO FIT YOUR DATA September 2005 First edition Add to Reading List Source URL: www.wolfram.com Language: English - Date: 2005-12-27 14:36:27 Statistics Artificial neural network Feedforward neural network Perceptron Statistical classification Radial basis function Types of artificial neural networks NeuroSolutions Neural networks Machine learning Cybernetics
213	Artificial Neural Networks Examination, March 2001 Instructions For each question, please select a maximum of ONE of the given answers (either A, B, C, D or E). You should select the one answer that represents the BEST p Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-06-07 09:38:12 Science Feedforward neural network Perceptron Artificial neural network Generalization error Backpropagation Hopfield network Supervised learning Pattern recognition Neural networks Machine learning Cybernetics
214	Journal of Machine Learning Research3817 Submitted 4/13; Revised 9/13; PublishedBudgetedSVM: A Toolbox for Scalable SVM Approximations Nemanja Djuric Add to Reading List Source URL: astro.temple.edu Language: English - Date: 2014-01-24 01:52:55 Support vector machines Learning Linear classifier Perceptron Stochastic gradient descent Least squares support vector machine Shogun Statistics Machine learning Statistical classification
215	Artificial Neural Networks – Lab 3 Simple neuron models and learning algorithms Purpose To study some basic neuron models and learning algorithms by using Matlab’s neural network toolbox. Add to Reading List Source URL: aass.oru.se Language: English - Date: 2005-02-08 05:38:24 Science Perceptron ADALINE Artificial neural network Hebbian theory Activation function Feedforward neural network Types of artificial neural networks Neural networks Machine learning Cybernetics
216	A Neural Architecture for Computing Acoustic-phonetic Invariants Elaine Tsiang Abstract The proposed neural architecture consists of an analytic lower Add to Reading List Source URL: www.ihear.com Language: English - Date: 1999-11-15 12:00:11 Anatomy Cerebrum Computational neuroscience Network architecture Neocognitron Speech perception Speech recognition Perceptron Tonotopy Mind Neural networks Cognitive science
217	Application of machine learning in industrial radiographic testing Add to Reading List Source URL: www.data-mining-tutorial.de Language: English - Date: 2009-10-09 07:20:40 Computational statistics Decision trees Computational neuroscience Pruning Backpropagation Supervised learning Perceptron Decision tree learning Multilayer perceptron Statistics Machine learning Neural networks
218	Distributed Confidence-Weighted Classification on MapReduce Nemanja Djuric Temple University Philadelphia, PA, USA Add to Reading List Source URL: labs.yahoo.com Language: English - Date: 2014-09-28 00:40:17 Statistical classification Distributed computing architecture MapReduce Parallel computing Machine learning Support vector machine Linear classifier Perceptron Apache Hadoop Statistics Computing Concurrent computing
219	Artificial Neural Networks Examination, March 2002 Instructions There are SIXTY questions (worth up to 60 marks). The exam mark (maximum 60) will be added to the mark obtained in the laborations (maximum 5). The total pa Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-06-07 09:38:12 Statistics Perceptron Artificial neural network Multilayer perceptron Activation function Backpropagation ADALINE Supervised learning Competitive learning Neural networks Machine learning Cybernetics
220	Artificial Neural Networks Examination, June/August 2003 Instructions There are SIXTY questions (worth up to 60 marks). The exam mark (maximum 60) will be added to the mark obtained in the laborations (maximum 5). The to Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-06-07 09:38:12 Statistics Perceptron Artificial neural network Multilayer perceptron Generalization error Backpropagation Supervised learning Statistical classification Pattern recognition Neural networks Machine learning Cybernetics

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