# The Newer Ones

**October 1, 2018**

In terms of solving problems, any thing or guideline that guides towards solving a problem, and not an instance of a problem is called an "Algorithm". Put it this way, any steps you follow in your brain to calculate a division (choosing my words very carefully), is an algorithm, because division is a problem, but say, dividing 21 by 7 or 100 by 30 are problem instances, and the exact steps you follow to solve these problems, are instances, not algorithms. Now since we're clear on that, let's talk about classical problems. These are problems that classical set theory and logic and therefore classical algorithms can solve. But some problems, especially optimization problems, which are usually finding a maximum or minimum are almost impossible to be solved using classical methods, usually because they are so slow. In such cases, we use methods that are a tad **Smarter** or more efficient. For instance, let's say you have a document with 2 million pages, if you look it up for a phrase or a specific page or paragraph, and you use the classic methods which **Guarantee **success at some point, and definitive success, it would take 2 million times N, N being the time it takes to look through one page to find what you're looking for. But if you had multiple people each randomly checking a page, they'd actually have a better shot since their chances of success improves as they go forward, since they get an idea which way to go, or what to look at next. This is a method or an algorithm called the Genetic Algorithm and algorithms based on this method are called Genetic algorithms.

Courses

**August 30, 2018**

It's been exactly half a month since I started studying for the GRE General, which I want to take, and hopefully ace soon. I've started studying for the verbal reasoning test, by memorizing every single word of Barron's 800 Essential and so far, I think I'm making progress, just not as fast. If you've been through this or can give me any recommendations, please continue reading.

Blog

# The Other Ones

**August 25, 2018**

I know, you might have never heard of it, and yeah, it isn't a thing. But it is about to be. This is something I've been thinking about the entire summer, and I'm gonna start working on it soon.

Projects

**August 8, 2018**

So it's been a while since I wrote something, and sometimes to be quite honest, I feel like I need to. Just a few days ago, a friend of mine was telling me that it wouldn't hurt to update this website once in a while. Well, you know what, he was right. So until I find something interesting to share in terms of my work, I'm gonna write about me.

Blog

**April 11, 2018**

Basically I have a very strange and unique taste of things when it comes to my major, and the field I've been most interested in since the age of 4, which is computers and Computer Science. For those who don't know, there's a difference between the two while they are connected. I did enjoy things like programming, solving problems and even for a while working with web services and servers, but Computer Science or CS, is far beyond that. Basically the fundamentals of CS has roots within logic and mathematics, and not much calculus, but rather set theory, matrices, algebra and analysis.

Courses

**February 1, 2018**

Well, in a few days, my 4th semester in college is going to begin, and I've picked some very interesting new courses for this semester.

Courses

**January 24, 2018**

The third semester came and went so quickly, it gives me a headache just thinking about it.

Courses

**January 6, 2018**

Data Mining is an interesting course I took this past semester, and really enjoyed. Today I want to talk about it a little, what it actually is, and how it's done. Basically data mining brings together subjects like machine learning, statistical analysis and basic programming in order to analyze data and obtain information from what is called a data set. A data set can be a spreadsheet, a database, an ASCII file or really any source of data, which is gathered into a single form, which is called a data warehouse.

Courses