Science, Data, & Analytics 📊

Data and number crunching, analysis and visualisation, machine learning, and how those things affect us human beings.

The Science, Data, and Analytisc specialist track focuses on the use of Python in data analysis, scientific programming and machine learning. If you’re processing and understanding data, be it statistical analysis, visualisation or machine learning then there’s a plethora of Python based tools available to you. This track is for people in the data science industry, in academia or generally interested in using Python to gain insights from your data.

Talks in this track:
  • Panel Discussion: Ethical AI - From talk to practice by Nigel Dalton, Fiona Milne, Arna Karick, Lizzie Silver
  • geospatial data and analysis is :exploding_head: by Gala
  • The Software Engineering Part of Data Science by Niño Eclarin
  • Streamlit - Build interactive data dashboards quickly by Jaimin Khanderia
  • Why the float did it NaN? by Jakub Nabaglo
  • Extracting data from Excel with Python by samuel oranyeli
  • dask-image: distributed image processing for large data by Genevieve Buckley
  • Model Selection with Python: An Introduction to Hyper Parameter Tuning by Patrick Robotham
  • Build your own data warehouse for personal analytics with SQLite and Datasette by Simon Willison
  • DevOps for Data Science? - automate the boring stuff and leverage the OSS ecosystem by Dr. Tania Allard
  • Interactive Mapmaking with Python by Sangarshanan
  • Tweaking the rise and fall of empires and economies by Bosco Ho

  • The Science, Data, & Analytics track is proudly sponsored by Snowflake.