Do-it-yourself Natural Language Processing for makers

by Susan Li

Machine Learning & Data Science

Susan Li walks you through deep learning methods for natural language processing (NLP) tasks using Python and open source libraries, using a live example. Methods include word2vec embedding, recurrent neural networks (RNN) and convolutional neural networks (CNN). This is a hands-on approach to framing a real-world problem to the underlying NLP tasks and building a NLP application using Deep Learning. If you are a data scientist or software developer with experience in Python who wants to develop natural language processing software, this talk is for you.

About the Author

I am Susan Li, the Sr. Data Scientist at Kognitiv where I specialize in machine learning and NLP. I’m passionate about helping organizations realize the potential of big data and advanced analytics, and helping individuals enhance skills in data literacy. I frequently write and speak about predictive analytics, machine learning and NLP for technical and general audience. In my free time, I can be found training for the next half marathon.

Talk Details

Date: Saturday Nov. 16

Location: Clipper Room

Begin time: 10:30

Duration: 55 minutes

Sign-up: Please sign up for this tutorial on the wiki here.