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. 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