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Understanding F-Beta For Model Evaluation - NBD Lite #29
Improve the way to evaluate your model classifier.
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Cornellius Yudha Wijaya
6 Ways to Use Python's enumerate for Better Loop Control - NBD Lite #28
Leverage in-built Python library to improve your works.
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Cornellius Yudha Wijaya
How to Perform Feature Selection with Scikit-Learn
How to select important features for your machine learning model
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Cornellius Yudha Wijaya
Why is Confidence Interval Important in Interpreting Regression Coefficient? - NBD Lite #27
The importance of uncertainty estimation
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Cornellius Yudha Wijaya
How to Visualize Missing Data Patterns with missingno in Python - NBD Lite #26
Gain insight from your Missing Data
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Cornellius Yudha Wijaya
NBD Lite #17-24 Podcast Summary
Lite Series podcast coverage from Pandas Plotting to Multi-Class Classification
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Cornellius Yudha Wijaya
14:53
Does SMOTE Add Noise to Imbalanced Data? - NBD Lite #25
Taking a look at the popular oversampling method
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Cornellius Yudha Wijaya
One-vs-All vs. One-vs-One. Which Multi-Class Classification Strategies is Better? - NBD Lite #24
Strategies to considers in multi-class problem
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Cornellius Yudha Wijaya
Understanding Netflix Long-Term Satisfaction Recommendation System
Breaking down the recommendation system
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Cornellius Yudha Wijaya
Python’s itertools for Memory-Efficient Iteration - NBD Lite #23
Efficiently handle large dataset iteration
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Cornellius Yudha Wijaya
Traditional Bootstrap and Block Bootstrap. What is the Differences? - NBD Lite #22
The differences in resampling technique.
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Cornellius Yudha Wijaya
Do We Trust Feature Importance Scores from Random Forests and XGBoost? - NBD Lite #21
Consideration when using the feature importance score.
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Cornellius Yudha Wijaya
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