NBD Lite #1-8 Podcast Summary

Hey guys! You might or might not know, but recently, I tried to launch my NBD Lite series.

It’s a short article series you can read in 3 minutes to improve your knowledge.

I want to experiment with new things again, so I've created a podcast that summarizes my Lite summary for the week.

So, it’s an AI-generated podcast based on the Lite series within the week 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!

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Source:

1. NBD Lite #1: Intro to Supervised Learning

2. NBD Lite #2: Common Classification Machine Learning Algorithms

3. NBD Lite #3: Easy Classification Model Deployment with FastAPI and Docker

4. NBD Lite #4: Effect of Min Samples Leaf on Tree Model Complexity

5. NBD Lite #5: Implementing Precision-Recall Curve Analysis for Evaluating Imbalanced Classifiers

6. Breaking Down the Classification Report from Scikit-Learn - NBD Lite #6

7. Comparing Model Ensembling: Bagging, Boosting, and Stacking - NBD Lite #7

8. Why K-Means Failed at Non-Convex Shape Data-NBD Lite #8

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