PyData Tel Aviv Meetup: Creating Meaningful Features from Clickstream Data - Shir Meir Lador

Predicting client financial behaviour is usually done by financial data sources - such as client financial history, bank and credit statements, etc. In this talk we will review a different type of data source for risk assessment - features engineered from clickstream data gathered by Mixpanel. We will discuss what kind of features can be generated from clickstream data and how to generate these features using Pandas, what is the benefit of these unconventional features, what are the different correlations of the features with user financial behaviour and how can you apply clickstream data analysis to your problems in general. In addition we will see how to be careful of data leakage and how to better understand our model's decision using model explanation tools like LIME. PyData Tel Aviv Meetup #6 10 August 2017 Sponsored by Oracle https://www.meetup.com/PyData-Tel-Aviv/ www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps