As I'm well into my 5th semester in college, I've come to appreciate the courses I've chosen to take together. This semester I'm taking Artificial Intelligence and Databases as I planned. Moreover, Soft computing is an area that I've begun to explore as Genetic Algorithms is another one of my courses as is Fuzzy Logic. As for machine learning, I've started with MLCC which is being offered by Google for free, but I think I'm going to leave it for next semester, since I'm going to take my last CompSci course then, Artificial Neural Networks which can basically be considered as a sub-category of ML.

The cherry on top of these is Linear Algebra upon which lots of different fields are built, and not just in computer science. As it primarily discusses matrices and their use, it also opens the door of algebra wide open to anyone taking the course. Starting by defining matrices and following by spaces and maps(or transformations), it efficiently discusses theories that can be proven through induction or matrices themselves, as maps and spaces can be considered matrices as well.

I'm also quickly learning how to program in Matlab in order to use it for linear algebra, as well as Fuzzy Logic and Genetic algorithms(GA), since they are a lot more easily implemented in Matlab and Python.

This semester, there's lots of room to not only learn but do research and find projects or subjects to work on. I've been trying to model and solve Rubik's cube using GA and PSO(yet another evolutionary algorithm like GA), optimizing its parameters using fuzzy controllers, but can't seem to achieve beyond a certain limit. It is a fact that evolutionary algorithms are good solutions for optimization problems, but up to a certain size. That is exactly what I've been struggling with, and I think I'll be more successful with Simulated Annealing(another algorithm).

I'll try to update the website as I go through, but can't promise anything with such a packed semester.

 

As always, thank you for reading, and stay tuned!