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SkillsCast

JupyterLab - Your Personal Data Science Workbench

12th March 2018 in London at CodeNode

This SkillsCast was filmed at JupyterLab - Your Personal Data Science Workbench

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.

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Thanks to our sponsors

JupyterLab - Your Personal Data Science Workbench

Markus Schanta

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.

SkillsCast

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:

Thanks to our sponsors

About the Speaker

JupyterLab - Your Personal Data Science Workbench

Markus Schanta

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.