This video discusses Week 1 of MLT - PCA
Be mindful while watching the video, watch with full focus and attention.
Ideally, sit with a pen and paper and solve with me, pause in between and ponder. Ask each and every small doubt in comments.
Happy learning!
Some Corrections:
At 16:20 the eigenvector with the highest eigenvalue is [1/sqrt(2), 1/sqrt(2)]
00:00 Why PCA?
00:34 Huge Data
01:20 Objective of PCA
02:08 Visual Intuition
02:53 Curse of dimensionality
03:37 Projections formula (Recap)
06:43 Finding the best projection
09:25 Two different formulations
11:05 Rayleigh Quotient Bound
12:40 PCA method summary
13:35 Example
#iitm
#mathematicsformachinelearning
#machinelearning
#iitmadras
#datascience
#optimization
#matrix
#studywithme
#pyqs
#pca
