Data Science in 30 Minutes: Examining Machine Learning Trends with Cloudera Research Engineer, Shioulin Sam

This FREE webinar will take place LIVE online on January 23rd at 5:30PM ET. Register below now, space is limited!

Join The Data Incubator and Shioulin Sam, Research Scientist at Cloudera Fast Forward Labs for the next installment of our free online webinar series, Data Science in 30 Minutes: Examining Machine Learning Trends

We will explore the latest and greatest in machine learning, including (but not limited to) semantic recommendations and multi-task learning. In regard to semantic recommendations, we will discuss how multi-modal embeddings – an emerging technique from deep learning – enable us to build a better system that actually understands content. We will also look at how multi-task learning – an approach in which models are trained to learn related tasks in parallel – is central to the notion of Software 2.0, and helps computers learn more the way we do. We will showcase both capabilities with a live demo of our prototypes.

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About the speakers:

Shioulin Sam is a research engineer at Cloudera Fast Forward Labs. In her previous life, she was an angel investor focusing on women-led start-ups. She also worked in the investment management industry designing quantitative trading strategies. She holds a Ph.D in Electrical Engineering and Computer Science from Massachusetts Institute of Technology.

Michael Li founded The Data Incubator, a New York-based training program that turns talented PhDs from academia into workplace-ready data scientists and quants. The program is free to Fellows, employers engage with the Incubator as hiring partners. Previously, he worked as a data scientist (Foursquare), Wall Street quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He completed his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall Scholar. At Foursquare, Michael discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup to focus on what he really loves. Michael lives in New York, where he enjoys the Opera, rock climbing, and attending geeky data science events.

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