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Articles by JeffHeaton (Articles: 4)

Articles: 4

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Average article rating: 4.83

Artificial Intelligence
17 Jan 2010   Updated: 17 Jan 2010   Rating: 4.69/5    Votes: 9   Popularity: 4.48
Licence: LGPL3    Views: 76,955     Bookmarked: 23   Downloaded: 2,150
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An introduction to creating neural networks with the Encog Framework for Java.
26 Jan 2010   Updated: 26 Jan 2010   Rating: 4.95/5    Votes: 32   Popularity: 7.38
Licence: CPOL    Views: 81,045     Bookmarked: 60   Downloaded: 4,066
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An introduction to creating neural networks with the Encog Framework for C#.
Machine Learning
16 Oct 2012   Updated: 16 Oct 2012   Rating: 4.88/5    Votes: 7   Popularity: 4.12
Licence: Apache    Views: 88,726     Bookmarked: 27   Downloaded: 1,353
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Use Encog genetic algorithms, simulated annealing, neural networks and more with HTML5 Javascript.
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Java
9 Jun 2010   Updated: 9 Jun 2010   Rating: 4.80/5    Votes: 8   Popularity: 4.33
Licence: LGPL3    Views: 177,192     Bookmarked: 22   Downloaded: 2,821
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Learn the basics of how to install and use OpenCL with Java, unleash the power of your GPU.

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United States United States
Jeff Heaton, Ph.D., is a data scientist, an adjunct instructor for the Sever Institute at Washington University, and the author of several books about artificial intelligence. Jeff holds a Master of Information Management (MIM) from Washington University and a PhD in computer science from Nova Southeastern University. Over twenty years of experience in all aspects of software development allows Jeff to bridge the gap between complex data science problems and proven software development. Working primarily with the Python, R, Java/C#, and JavaScript programming languages he leverages frameworks such as TensorFlow, Scikit-Learn, Numpy, and Theano to implement deep learning, random forests, gradient boosting machines, support vector machines, T-SNE, and generalized linear models (GLM). Jeff holds numerous certifications and credentials, such as the Johns Hopkins Data Science certification, Fellow of the Life Management Institute (FLMI), ACM Upsilon Pi Epsilon (UPE), a senior membership with IEEE. He has published his research through peer reviewed papers with the Journal of Machine Learning Research and IEEE.