ML enthusiast, a Cybersecurity expert.
Well, this is my first ever published content. I am a writer; I write academic content, sometimes technical articles. I can say this is more of a personal opinion than a statistically analyzed interpretation.
Over my years of learning programming, I grew to be an enthusiast of Artificial Intelligence. I started coding at 16. This was before I joined college. I learned Java; without a backbone or understanding of programming languages. As expected, I dropped it after a week. That was after I saw a meme of the different "Hello World" programs.
I started Python and loved it. I could write code much faster, instead of spending too much time understanding the syntax. Second, I built my source codes from scratch using functions (Java made me hate classes). I did some game development with Python and a bit of software development. My first Python project could open major productive applications under one working window using Tkinter. The link to the project is https://github.com/mundiakaluson/ALL-UNDER-ONE-AU1-
When I joined college, I the basics of machine learning with some mentoring from my lecturers, and I got to it! My first model was made of dummy numbers. It was a linear regression model. I was happy the score was 98 or something. I moved on to Logistic Regression and finally started building Random Forests. It was the right road; I got used to machine learning so fast because I started coding like a year ago.
After eight months of machine learning, I dropped it. So why now? Frankly speaking, many experts think this topic is irrelevant to the debate. Coding algorithms is a tough job, for starters at least. I was good at building models and making them efficient. I loved what I was doing.
Coming to the climax (where I started contributing to real projects), I contributed to a project dealing with training a model that would implement the MD5 algorithm to become much efficient. We did not finish that project. I got to interact with cybersecurity experts and become familiar with a bug bounty. Moving on to research on cybersecurity, I discovered that Python was the primary language. I smiled on my screen at 3 in the morning. Then I looked at network scanners and came across scapy, a Python module used in networking. I created a quick network scanner (which I have greatly improved as of now). I figured out that I like breaking stuff. In artificial intelligence, we don't break stuff, and we fix stuff.
My final verdict comes in the way you want to progress in the world of computer science. If you are a fix-guy or a repair main, make machines learn if you like breaking stuff and knowing how and what they are made from, then get into cybersecurity. I was happy with machine learning (and still happy), but I was not doing what my mindset was after. I hope you enjoy my first article. It's not perfect, but it's at least a try :)
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