NBD Lite #17-24 Podcast Summary

Hey guys! The next batch of NBD Lite series has already reached number 124, 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.

Using NotebookLM, I produce an AI-generated podcast based on the Lite series for #17 to #24, hosted by two people who talk to 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. 5 Pandas Plotting to Improve Your Data Workflow - NBD Lite #17

2. 6 Common Hyperparameter Optimization Techniques- NBD Lite #18

3. Python Packages for Interactive Data Analysis - NBD Lite #19

4. Is It Necessary For Feature Scaling in Tree-Based Models? - NBD Lite #20

5. Do We Trust Feature Importance Scores from Random Forests and XGBoost? - NBD Lite #21

6. Traditional Bootstrap and Block Bootstrap. What is the Differences? - NBD Lite #22

7. Python’s itertools for Memory-Efficient Iteration - NBD Lite #23

8. One-vs-All vs. One-vs-One. Which Multi-Class Classification Strategies is Better? - NBD Lite #24