General Sequence Learning Using Recurrent Neural Nets
March 12, 2015 / Machine Learning, Tutorials
Our Head of Research, Alec Radford, recently led a workshop on general sequence learning using recurrent neural networks at Next.ML in San Francisco. Next.ML was created to teach the latest actionable machine learning techniques that you can use right out of the workshop.
The upcoming Next.ML workshop will be in Cambridge, MA at the Microsoft NERD Center on April 27.
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 such as 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.