The AI Path I Never Chose (But Love)

Hey everyone. I'm Manikanta. At present, I am pursuing an M.Tech with a background in CSE with a specialization in AI&DS. So, as an upcoming "something," I want to express myself and show/let y'all know about me through these blogs, whatever they may be called. So here we will start from my experiences where I learned A, B, C, D, ... in AI. It all began in my B.Tech. It was then that I wanted to pursue my specialization in IoT, an interesting topic that I wanted to master, but the world had some other way around things that made me choose AI&IPA (Artificial Intelligence & Information Process Automation). Initially, I was not interested in learning these things, but what can we do when we have credits to complete, a course to pass, and a placement to place? In my 3rd year odd semester, we have 2 professional electives, which are machine learning and artificial neural networks. The two subjects changed the way I learn something. Coming to the subject's pew... machine learning (ML), man, I loved the way they used and pushed probability and worked with it. ANN (my personal favorite) is one of the subjects where I don't want to bunk the class. The way the neurons transform the weights, the way we calculate the values, and the way we work with activation functions. A chef's kiss from me to the person who even thought of working with something that is this interesting. Then, the next semester, I had 3 subjects that I felt were worth studying: deep learning (DL), natural language processing (NLP), and cognitive computing. Let's discuss them in order. First, My love for deep learning: we never get a chance to calculate or work more on text or speech, but the clarity I got from working on images is peak level. The professor who taught me deep learning is my guide too, so with that, I got a chance to work and write a paper with her. I think this topic needs a separate blog/something. Coming back to the subject, the way I got to know about CNN and its various versions or extensions of CNNs, GANs, and autoencoders was something I never thought of; there is something like this happening, and we can compute something like this. Like you, I probably can't assume I got to know how they work, like the processing of hidden layers and their process throughout the output layer kept my mouth open even though I learned them and worked with them. Natural Language Processing (NLP) is quite an interesting subject, both theoretically and practically, but I didn't get enough chance to explore it practically. Cognitive Computing (CC): To be honest, in my entire bachelor's, this is the only course that I never knew what I was even studying/looking at. The professor for Cognitive Computing came from a different background, and his distinctive accent added a unique flavor to his lectures. His extensive experience in the field was clear, though I found that his teaching style was a bit challenging for me at times. But most of this course revolves around ML and NLP. I got to know something about NLP practically through this course. That is how I got an interest in AI and how I started getting along with the things that got in my way, which I didn't think I would. See you the next one with some topic that interests you, I guess.