General Sequence Learning using Recurrent Neural Networks





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Published on Feb 17, 2015

indico's Head of Research, Alec Radford, led a workshop on general sequence learning using recurrent neural networks at Next.ML in San Francisco. His presentation and workshop resources are available here for free.

Recurrent Neural Networks hold great promise as general sequence learning algorithms. As such, they are a very promising tool for text analysis. However, outside of very specific use cases like handwriting recognition and recently, machine translation, they have not seen widespread use. Why has this been the case?

In this workshop, Alec will introduce RNNs as a concept. Then you'll sketch how to implement them and cover the tricks necessary to make them work well. With the basics covered, we will investigate using RNNs as general text classification and regression models, examining where they succeed and where they fail compared to more traditional text analysis models.

Finally, a simple Python and Theano library for training RNNs with a scikit-learn style interface will be introduced and you'll see how to use it through several hands-on tutorials on real world text datasets.

Next.ML was created to help you use the latest machine learning techniques the minute you leave the workshop. Learn from industry-leading data scientists at Next.ML on April 27th, 2015 at the Microsoft NERD Center -- for more info, visit http://Next.ML

Passage - https://github.com/IndicoDataSolution...
Presentation Slides - http://www.slideshare.net/indicods/ge...


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