Titanic Survival Prediction with Python & KNN: A Step-by-Step Coding Tutorial

This tutorial provides a hands-on guide to implementing the K Nearest Neighbours (K&N) algorithm using Google Collab. It covers the basics of using Google Collab, explores a Titanic passenger data set, and walks through data preprocessing steps. The video demonstrates training a K&N model, evaluating its accuracy, and visualizing results using PCA. It also discusses optimizing the number of neighbors for better accuracy.

What steps are involved in encoding categorical features in the data set?

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What is the accuracy of the model as mentioned in the tutorial?

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How do you determine the optimal number of neighbors in the K&N algorithm?

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