In this second video, we motivate why it is useful to reduce the dimensionality of your data, and describe how this can be done linearly, using a transformation matrix. We describe a setup whereby we also use the transpose of the transformation matrix to attempt to reconstruct our original data from a lower dimension. This allows us to compute reconstruction error to assess how good the transformation is as a whole.