Speaker: Amber McKenzie

Data Scientist @DialogTech

Amber McKenzie is a Data Scientist with DialogTech. She has a masters degree in Linguistics and a Ph.D. in Computer Science from the University of South Carolina and specializes in natural language processing (NLP). She previously worked for the Computational Data Analytics group at Oak Ridge National Laboratory and as the Lead Data Scientist for text analytics for a start-up data analytics firm. Amber has over 8 years experience in NLP working in varied projects spanning from helicopter maintenance to children services and in multiple sectors, including federal law enforcement, state government, military, commercial industry and healthcare.

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Workshop: Introduction to NLP using NLTK and Python

Location: Bayview A

Day of week: Friday

Duration: 1:00pm - 4:00pm

Blogs, product reviews, news articles, physician reports, tweets - the digital universe provides a wealth of data analysis resources in the form of relatively untapped unstructured text.

This hands-on session will introduce attendees to the Natural Language ToolKit (NLTK), a Python-based library with a robust set of natural language processing (NLP) functionality.

The talk will guide attendees through several modules designed to demonstrate the use of various NLP techniques to analyze and explore real-world text-based data sets. Attendees will leave the talk equipped with the foundation and techniques to extract meaningful and useful information from their own data.

Key takeaways:

Introduction to natural language processing and text analytics
Hands-on experience with a robust NLP library in python
Application of NLP techniques on real-world data

Tracks

Monday Nov 7

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Tuesday Nov 8

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Big Data Meets the Cloud

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Wednesday Nov 9

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Stream Processing

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UX Reimagined

Bots, virtual reality, voice, and new thought processes around design. The track explores the current art of the possible in UX and lessons from early adoption.

SCHEDULE

Find Amber McKenzie at

Workshop: Introduction to NLP using NLTK and Python

Tracks

Monday Nov 7

Tuesday Nov 8

Wednesday Nov 9

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