In this video, I compare the kaggle and github for data science portfolios. Both are great platforms, but which is best for you?
Kaggle and github are the two many ways that you can showcase your work as a data scientist or aspiring data scientist. You also constantly hear me blabbering about how valuable each of these platforms are. In this video, I will compare the two platforms to determine which is the best place for you to host your data science portfolio on.
Kaggle is arguably the largest data science community out there. It started as a place where people could go to compete against each other in data science competitions. It still has these competitions, but now it has evolved into a one stop shop for data science learning, awesome datasets, and engaged forum. On Kaggle, you have a profile where you can earn rankings for sharing your work and placing well in competitions.
Github, on the other hand, is more focused on function. Github is one of the hosting platforms for the versioning control system called git. Git allows you and your team to keep track of the changes in your code. This can be extremely valuable when you have multiple people working on a project. Git has also evolved into a place where you keep and maintain all of the code that you write. Many developers use their github profile & repositories as a living documentation for all they have done.
Kaggle:
+ Simple Reward System
+ Great Community + Discoverability
+ Clear Focus on Data Science
- Limited ways to share
- Limited in the skills you can showcase
Github:
+Shows you know GIT
+ Highlights Documentation
+ Illustrates More Diverse Skillset
+ More Flexibility
- More difficult to use
- Greater time commitment
- Additional skills like git & markdown