During this talk, Reece Heineke will demonstrate in one hour how you can use Python to explore financial time series data, apply a number of machine learning models and find the best fitting one.
Starting with a generated data set, we will evaluate ways to make the data quantity manageable, explore the data visually, do some basic cleaning and ultimately use supervised learning to determine which model is the most appropriate for the data.
Reece Heineke is a data scientist and engineer working at the fintech startup Credibly which provides capital to small businesses. He has a PhD in Astrophysics from the University of Cambridge in the UK, and a BA in Physics from Reed College in Portland, OR. He now lives in NYC, and is always keen on discovering new tools and techniques to explore data. Reece is excited to join the Academy’s team to be able to teach once again.