Kyle is a Data Scientist and podcast host. In this meeting he will discuss using machine learning within the audio domain.
6:30 PM Doors open
6:30 PM - 7:00 PM Snack and drinks served
7:00 PM - 8:00 PM Presentation and Q&A
8:00 PM - 8:30 PM Mingling
8:30 PM Doors close
Note: This event is being held both at a different location and different time than previous events. I hope the new time will allow more people to attend.
Title: Machine Learning for audio data
Kyle Polich is a data scientist with a special interest in machine learning and artificial intelligence. He's worked in a variety of industries including adtech, market research, ecommerce, and industrial optimization. He hosts the Data Skeptic podcast, a weekly show with short tutorials, interviews with domain experts, and stories about how data effects our world.
Most non-trivial machine learning projects require technical expertise in algorithms as well as some domain knowledge. While speech understanding remains a difficult problem, speech detection and other interesting audio-related tasks can be solved using machine learning today. This talk is aimed at machine learning practitioners with no background in audio engineering. Core concepts and techniques will be covered. Kyle will discuss why certain problems remain hard. The codebase and process for creating a speaker detection system will also be covered.
Parking and directions:
The best street parking options will be on Electric Avenue and in the neighborhood east of Electric Ave. There is also metered parking on Irving Tabor.
How to find us: Enter the building in the alley at 1625 S Irving Tabor Ct, Venice, CA 90291, through the double doors under the lit ZEFR sign.