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.
YOU MAY ALSO LIKE:
- Vega – A Grammar of Interactive Graphics (SkillsCast recorded in July 2018)
- Fast Track to Chaos Engineering with Russ Miles (in London on 1st - 3rd July 2019)
- Damjan Vujnovic's Angular Workshop (in London on 3rd - 5th July 2019)
- Infiniteconf 2019 - A one-day community celebration of Big Data, Machine Learning and AI (in London on 4th July 2019)
- FullStack London 2019 - The Conference on JavaScript, Node & Internet of Things (in London on 10th - 12th July 2019)
- IWDS 23: Intro to Natural Language Processing (NLP) - 1/2 (in London on 24th June 2019)
- Keynote by Bruce Lawson on How To Make Loveliness: an HTML Treasure Hunt (in London on 24th June 2019)
- The Power of Linux Virtualization with Cloud Native (SkillsCast recorded in June 2019)
- Upgrading to Django 2.2 (SkillsCast recorded in June 2019)
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.
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)
- Fast Track to Chaos Engineering with Russ Miles (in London on 1st - 3rd July 2019)
- Damjan Vujnovic's Angular Workshop (in London on 3rd - 5th July 2019)
- Infiniteconf 2019 - A one-day community celebration of Big Data, Machine Learning and AI (in London on 4th July 2019)
- FullStack London 2019 - The Conference on JavaScript, Node & Internet of Things (in London on 10th - 12th July 2019)
- IWDS 23: Intro to Natural Language Processing (NLP) - 1/2 (in London on 24th June 2019)
- Keynote by Bruce Lawson on How To Make Loveliness: an HTML Treasure Hunt (in London on 24th June 2019)
- The Power of Linux Virtualization with Cloud Native (SkillsCast recorded in June 2019)
- Upgrading to Django 2.2 (SkillsCast recorded in June 2019)
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.