In this session, Markus Schanta will introduce JupyterLab as a data science/research environment and show off its most useful features. He will also show you how to set up your own instance of JupyterLab either locally or in the cloud on Amazon AWS.
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.
YOU MAY ALSO LIKE:
- Vega – A Grammar of Interactive Graphics (SkillsCast recorded in July 2018)
- Leonardo De Marchi's Deep Learning Fundamentals (in London on 22nd - 23rd October 2019)
- Clojure eXchange 2019 (in London on 2nd - 3rd December 2019)
- Security in the Age of Big Data (Data Anonymisation & Encryption) (in London on 21st October 2019)
- IWDS 26: Evaluating and improving our Data Science models (in London on 21st October 2019)
- Going Multicloud with Serverless (SkillsCast recorded in October 2019)
- Automating Elaborate-Transform-Load for Busy Data Scientists (SkillsCast recorded in October 2019)
JupyterLab - Your Personal Data Science Workbench
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.