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Chicago Python Data Special Interest Group presents Natural Language Processing!

Join us on Wednesday, June 17th for a night of talks about Natural Language Processing (NLP). This event will be Live Streamed to our YouTube Channel: https://www.youtube.com/watch?v=tD4T1bQWOM8

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AGENDA
6:00 - Broadcast starts on YouTube
8:00 - Estimated end time

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Our talks:

¡Escuincla babosa! A Python Deep Learning Telenovela
by Lorena Mesa

Telenovelas are beloved for their over the top drama and intricate plot twists. In this talk, we'll review popular telenovelas to synthesize a typical telenovela arc and use it to train a deep learning model.

What would a telenovela script look like as imagined by a neural network? To answer this question, we'll examine three Python deep learning frameworks - Keras, PyTorch, and TensorFlow - to determine the process of translating a telenovela into a neural network and ultimately determine which one will be best for the task at hand. Be prepared for amor, pasiòn, and y el misterioso!

Bio:
Political scientist turned coder, Lorena Mesa is a GitHub data engineer, Director and Vice-Chair, Elect on the Python Software Foundation, and PyLadies Chicago co-organizer. Lorena's time at Obama for America and her subsequent graduate research required her to learn how to transform messy, incomplete data into intelligible analysis on topics like predicting Latinx voter behavior. It's this unique background in research and applied mathematics that drove Lorena to pursue a career in engineering and data science. One part activist, one part Star Wars fanatic, and another part Trekkie, Lorena abides by the motto to "live long and prosper".

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Gathering Insights from Audio Data
by Ryan Bales

Data comes in many shapes and sizes. In this session, we’ll look into the process of converting audio files into valuable data. We’ll go over the different types of audio formats and how format and type of audio plays a role in the quality of the outcome. We’ll go over different transcription options available today and provide a demo of converting audio data into text. We’ll review ways of storing and searching text data at scale using open source tools and Natural Language Processing (NLP) techniques. Going further we’ll explore different techniques for building machine learning models on the transcribed text data. You’ll leave this session with a firm understanding of how-to take audio data and convert it into actionable insights.

Bio:
Ryan Bales is the Director of Data Science and Analytics at DialogTech. He’s an active member of the Cleveland technology community, CLE Data Science and R Meetup groups. Ryan is a content contributor and class facilitator for the Python Data Science course track at DriveIT. When not writing code or trying to learn more about data science you can find Ryan trying to not lose at online video games. Ryan lives in Cleveland, Ohio.

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