Matrix Mania

From matrix-averse, I am now officially a convert to the cult of the matrix. One of my deepest regrets is not giving matrix mathematics the love that it sorely deserves. Now, I am working with them all the time and I felt so much regret that I did not take those linear algebra lectures in college seriously! Ohhh, the pain of missed chanecs!

Now I needed the refresher more than ever. I can’t turn back time but I can speedread my way to it. I am almost done with the my refresher literature so that I can finally go work on coding with TENSORS in full blast using R.

After getting hooked on all these technical explorations, I had a ‘Where have you been all my life?’ thought bubble in my head! It’s just crazy how late I began in this! It’s just amazing, picking things that Einstein in his genius picked from scratch in his time. It’s exciting and I feel sad that there are few people who appreciate this. Photo files make use of pixel matrices. Cryptography makes use of bit matrices. R programming handles gazillions of big data matrices. LiDAR data uses matrices extensively in automation and machine learning. It’s just great and it is in everything, even in things that people casually just disregard. And there is more than 2 dimensions in a matrix. It can run infinitely and converge somewhere in time and space.

Things move around in a matrix like with infinite possibilities of breaking it down and solving it. It’s a typical “there are many ways to skin a cat” problem. You are not restricted to a single method. You can reduce a huge matrix into blocks, or lower and upper triangular matrix breakdowns, or employ the use of another vector space. I am really genuinely enjoying this.

Resources are everywhere. (I actually need help trimming down my reading list. I have enough books to last me two lifetimes, digitally and non-digitally.) The challenge is really in just making time to access these resources and maximize them. A project-based learning is more apt because you can solve things one at a time and increase the complexity of the problems progressively through it.