The Jupyter notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. It's a great research environment for finance and machine learning applications.
The talk does not require extensive knowledge of Python, Jupyter or AWS. We will aim to provide useful information for beginners as well as people who are already somewhat familiar with these technologies.
All the coding will be published live to GitHub, so you can follow on your own laptop if you wish, or revisit afterwards.
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Markus Schanta is a data scientist with professional experience working for large hedge funds and investment banks. He uses mathematics, statistics and computer science to turn data into actionable insights. Originally from Austria, he holds a BSc from the Vienna University of Technology and an MS in Machine Learning from Columbia University in New York where he had been awarded a Fulbright Scholarship.