Data Science, Artificial Intelligence, K Means, Audience Engagement, Python.
in which the distance between data points in high-dimensional space loses meaning, making it difficult to accurately cluster the data. By reducing the number of features using PCA, we can mitigate the curse of dimensionality impact and improve the accuracy and efficiency of our K-means clustering