Reinforcement learning common use cases, recommendation engine, productivity - Susan Shu Chang the data scientist show#039

Daliana's Game

Susan Shu Chang is a principal data scientist at clearco, helping ecommerce founders' by building machine learning-powered investing. In her previous role, she developed the company’s very first ML powered website recommender system, deployed to millions of customers, and created a custom OpenAI Gym environment for a reinforcement learning project in production. She is also the founder and developer of Quill Game Studios, selling ~10k copies of the debut game in 6 months. She has given talks at PyCon Canada,Toronto Machine Learning Summit (TMLS), and more. She writes about her career journey and learning on https://www.susanshu.com/ If you like the show subscribe to the channel and give us a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com/ for more on data science.

Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu/

Daliana's Twitter: https://twitter.com/DalianaLiu

Highlights 

(00:00) Intro 

(00:01:29) from economics to data science 

(00:07:23) reinforcement learning (RL) 

(00:20:00) recent reinforcement learning use cases 

(00:27:28) reinforcement learning for social media's recommender system 

(01:04:42) common mistakes when productionizing models 

(01:08:30) principal data scientist's day-to-day

(01:14:05) what productivity really means 

(01:21:04) productivity tips 

(01:41:48) books and blogs on productivity

To listen to explicit episodes, sign in.

Stay up to date with this show

Sign in or sign up to follow shows, save episodes, and get the latest updates.

Select a country or region

Africa, Middle East, and India

Asia Pacific

Europe

Latin America and the Caribbean

The United States and Canada