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A Primer on Neural Network Models for Natural Language Processing

  • Anchor, 1st floor, CIC Boston 50 Milk Street Boston, MA, 02110 United States (map)

Interest in Neural networks is growing with many areas from image recognition to speech processing reporting impressive results. With advances in software and hardware technologies, and interest in AI based applications growing, it is time to understand neural networks applied to natural language processing better!

In this workshop, we will discuss the basics of neural networks and natural language processing and discuss how neural approaches differ from traditional natural language modeling techniques. We will review a bit of mathematics that goes into building neural networks and natural language modeling tasks. We will also illustrate through a case study Sentiment analysis using Deep Learning architectures. Functional Demos will be presented in Keras, a popular Python package with a back-end in Tensorflow.

This workshop is FREE and is a part of the upcoming QuantUniversity NLP workshop (

6.00-6.30 : Networking and Refreshments
6.30-7.15 : Workshop

Planned topics:
- Intro to Natural Language Processing
- Intro to Neural Networks and Deep Neural Networks
- Networks that “understand” language!
- Embeddings: clever representation of words
- Recurrent Neural Networks: remembering history
- Encoder-Decoder architectures
- So many models! So little time! - QuSandbox