NYC Women in Machine Learning & Data Science

Event space sponsored by Galvanize. Food and refreshments sponsored by K2 Data Science Please bring a laptop as this is a hands-on workshop. Knowledge of Python (with Pandas and Scikit-learn) is required.   Agenda: 10:00am – 12:00pm: Talk by Ty Shaikh 12:00pm – 1:00pm: Lunch 1:00pm – 3:00pm: Breakouts During the morning session Ty will describe recommender systems using collaborative filtering and go over some use cases.   Participants will work in teams on a recommendation problem using a public data set (MovieLens rating data, Last.fm user listening data or Expedia hotel search data). Students will be able to try different recommendation engine approaches in Python and compare the predictions. At the end of the workshop, each team will present their findings. Ty Shaikh, Teaching Assistant at K2 Data Science, @K2DataScience Ty Shaikh currently works as a…


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