07-13, 11:35–12:05 (Europe/Dublin), Liffey Hall 2
In this talk, I will give you tips and practical advice on what steps to follow and how to plan your data science project to avoid making the most common mistakes during its development.
Despite my limited experience delivering data science projects, I have learned how to avoid certain mistakes. In this talk I will teach you how to prevent them and save you lots of headaches.
In this talk you will learn tips on:
- Defining requirements
- Outlining a data science project
- Reproducibility and Readability checklist
- Best practices for writing Documentation
- Useful python tools
- Tips on presenting your findings
This is a talk is intended for beginner audience.
learn how to avoid the common mistakes when starting a data science project
Expected audience expertise: Python –none
Expected audience expertise: Domain –none
Business Intelligence analyst at NHS and machine learning enthusiast. Sara is active in the Python community and efforts in empowering women in tech by leading and organizing events focused on increasing the visibility of women in stem careers.