Supervised machine learning requires large labeled datasets, a prohibitive limitation in many real-world applications. But what if machines could learn with fewer labeled examples?
Shioulin Sam explores and demonstrates an algorithmic solution that relies on collaboration between humans and machines to label smartly, and discuss product possibilities for various verticals.
Shioulin Sam is a research engineer at Cloudera Fast Forward Labs, where she bridges academic research in machine learning with industrial applications. Previously, she managed a portfolio of early stage ventures focusing on women-led startups and public market investments and worked in the investment management industry designing quantitative trading strategies. She holds a PhD in electrical engineering and computer science from the Massachusetts Institute of Technology.
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