Hey Folks! I finally got around to watching a bunch of the talks and found several of the talks useful for improving my Python coding skills in general and/or in the context of doing Data Science. Here are some interesting talks from PyCon 2020:
- Beautiful Python Refactoring video. The talk was simple but powerful in demonstrating the process of refactoring in Python.
- Docker and Python: making them play nicely and securely for Data Science and ML. Talk discussed why use Docker in general and for machine learning, and how to manage security and performance while using Docker. It’s a great introduction to Docker – motivating its use case as a Data Scientist. Some tips that she shared include getting standard project templates from cookie cutter data science. Another was to use repo2docker to build a docker based on a local or remote repo. It was also very engaging.
- Small Big Data: Using Numpy and Pandas When Your Data Doesn’t Fit In Memory. This talk expanded my knowledge of Numpy and Pandas for handling small big data, which happens more than you think.
Pro-tip: Watch at ~1.5 speed to save time!
PyCon 2020