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

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.

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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