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End-to-end notebook

25 min applied40 min research2 curated resources

Using a loan dataset: clean with pandas, visual EDA with seaborn, standardise with NumPy, train logistic regression with your own gradient descent, compare to scikit-learn, report metrics with bootstrap CIs. Concepts: Integrates Python, NumPy, pandas, Matplotlib/Seaborn, gradient descent, probability and statistics

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