Data Dreamland, Subash Palvel, Data Science, Dimensionality Reduction, Machine Learning.
PCA, t-SNE, LDA, and autoencoders. Each technique has its own strengths and applications, and the choice of technique depends on the specific problem and dataset at hand. By understanding and applying these dimensionality reduction techniques, we can gain valuable insights from complex data and