AI, Dimensionality Reduction, Machine Learning, Python, Data Science.
when the assumption of normally distributed classes and equal covariance matrices holds. 3. SVD (Singular Value Decomposition) Use Cases: 1. When dealing with sparse data or missing values. 2. In collaborative filtering for recommendation systems. 3. SVD is also applicable in data compression and