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algorithms. Encog contains classes to create a wide variety of networks, as well as support classes to normalize and process data for these neural networks. Encog trains using many different techniques. Multithreading is used to allow optimal training performance on multicore machines.
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Encog can be used for many tasks, including medical and financial research. A GUI based workbench is also provided to help model and train neural networks. Encog has been in active development since 2008.
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352:: An open-source deep learning library written for Java/C++ w/LSTMs and convolutional networks. Parallelization with Apache Spark and Aeron on CPUs and GPUs.
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Benchmarking and
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Basic Market
Forecasting with Encog Neural Networks (DevX Article)
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An
Introduction to Encog Neural Networks for Java (Code Project)
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http://www.biomedcentral.com/content/pdf/1471-2105-11-37.pdf
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http://www.jmlr.org/papers/volume16/heaton15a/heaton15a.pdf
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470:Java (programming language) software
382:D. Heider, J. Verheyen, D. Hoffmann
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409:http://www.heatonresearch.com/encog
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411:Description of Encog Project.
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180:Support Vector Machines
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201:ADALINE Neural Network
465:Free science software
294:Competitive learning
176:Hidden Markov Models
263:Training techniques
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130:Apache 2.0 Licence
299:Hopfield Learning
216:Boltzmann Machine
172:Bayesian Networks
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329:: another
86:Written in
75:Repository
61:2017-09-01
321:See also
136:Website
125:License
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340:FANN
335:Java
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