Dimensionality Reduction (PCA Vs. LDA) Lecture
In this lecture, we will address the problem of feature engineering. In particular, we will focus on two feature extraction methods: Principal Component Analysis (PCA) and Linear Dimensionality Analysis (LDA). We will derive in detail the algorithms for both PCA and LDA, then we will compare and contrast both methods highlighting their strengths, limitations and applications.
Event Expiry Date - Saturday, January 23, 2021