Hey guys! The next batch of NBD Lite series has already reached the number 16, and here is the podcast summary.
The NBD Lite series is a short article series you can read in 3 minutes to improve your knowledge.
As I mentioned in the previous post, I want to experiment with new things, so I've created a podcast summarizing my Lite summary for the week.
So, it’s an AI-generated podcast based on the Lite series for #9 to #16 and hosted by two people who talk with each other.
If you like listening instead of reading, this podcast might help you learn!
Don’t miss it!
Source:
* Speeding Up Pandas with .apply vs. Vectorization - NBD Lite #9
* 8 Advance Feature Engineering For Machine Learning - NBD Lite #10
* 7 LLM Generation Parameters To Know - NBD Lite #11
* Understanding Data Leakage in Machine Learning - NBD Lite #12
* Data Science Alternative Career Path -NBD Lite #13
* Chi-Square Test for Feature Selection in Classification -NBD Lite #14
* Standardization vs Normalization: The Feature Scaler Role - NBD Lite #15
* Data Versioning Workflow With DVC - NBD Lite #16
