Fighting COVID with Python
summary
Demonstrates how Python and the PyData ecosystem were used to combat COVID-19 by describing data management, processing, analytics, and visualization workflows. Covers concrete tools and languages in that ecosystem (Python, and mentions related languages like Julia and R) and discusses best practices and approaches for building reproducible, community-driven data science pipelines for pandemic analysis.
AI-written summary · about
chapters (13)
- 0:00COVID research intro
- 3:21National COVID-19 database
- 6:14Data security and privacy
- 9:03Raw data to datasets
- 12:17Standardizing medical measurements
- 15:52Sharing data with researchers
- 18:12Patient survival models
- 22:01Ventilation settings and outcomes
- 24:52Domain-specific ML models
- 27:46Next steps and future research
- 30:43Standardizing medical terminology
- 32:55Doctors and data scientists
- 34:03Q&A
related talks
33mPython and Data Storytelling to the Rescue: Let's Avoid More Deaths by...
36mPython in Medicine: analysing data from mechanical...
33mData Science & Data Visualization in Python
45mPython useRs
37mThe Python Ecosystem for Data Science: A Guided Tour
01h 31mModern scientific computing and big data analytics in Python
22mLet’s make the world a better place: Python for Social Good
29mHow data science shortened the COVID-19 pandemic by 2 months