A Large Number of Parameters, Doesn't Mean You have a "High Dimensional Problem": A Lesson on… A Large Number of Parameters, Doesn't Mean You have a "High Dimensional Problem": A Lesson on…

I believe understanding fundamental concepts is crucial when it comes to learning something advanced. Because the fundamentals are the basis where you build your advanced knowledge on top of. If you put more things on top of the weak basis, it could break apart in the end, meaning you end up not fully understanding any of the materials you learned. Then you might need to go back again to learn the fundamentals before going back to learn the most exciting advanced materials which could be time consuming. Linear Algebra is one of the fundamental topics that you should be very comfortable with.

Singular Value Decomposition (SVD) is another type of decomposition. Unlike eigendecomposition where the matrix you want to decompose has to be a square matrix, SVD allows you to decompose a rectangular matrix (a matrix that has different numbers of rows and columns). This is often more useful in a real-life scenario since the rectangular matrix could represent a wide variety of data that's not a square matrix. First, let's look at the definition itself. As you can see, SVD decomposes the matrix into 3 different matrices.