I’m writing this just to leave some clarification as to where exactly I’m starting. Identifying where you’re starting might help with understand which parts you can do well and which ones you need improve on, such that you can learn whatever that is you want to.
Here’s my list of things related to Machine Learning that I already understand, have, and/or use:
Data: Now, this one is slightly more complicated than it sounds. When I say data, I mean everything you do with, like, data processing, data transformation, data cleaning, data engineering, data storage, and everything in these lines. I understand a good amount of things about data because I had the chance to work with several projects that led to me to understand how to deal with data, and I’ve learnt more through watching and studying projects that my friends and colleagues worked on, which had different (often times bigger) data problems than I have.
Machine Learning: I kinda understand some machine learning concepts intuitively, thanks to my Data Scientist friend, Naveen, who used to patiently answer every question I had about all the ML stuff he used to build in the hackathons we’ve been to.
Python: This is the most used language for machine learning work. It’s super easy to learn and I used to code in Python for fun before I joined college.
Math: Well, I’m not a big fan of math but I always try to correlate math to the real world, and I have a pretty solid understanding of it, and I’m confident that I can learn whatever is necessary (if at all it is), to understand certain things deeper.
Git & GitHub: For keeping track of all the projects code. I’ve been using this ever since I was in college and I still use it now at work.
C++: Helpful for doing machine learning on tiny hardware devices like Arduino (More on this later).
(Optional) Hardware: Experts at Harvard have been saying that the future of AI and ML is on-device. That includes tiny devices like mobile phones, Arduino devices, etc. I already have an Arduino, a Camera sensor, and a bunch of tiny PCBs to experiment with ML on tiny hardware (And I’ve even tried it before).
I think I have all the things I need to learn and understand ML and build cool things with it. Most of it is here because I’ve previously tried to learn ML but only passively.
If you’re reading this, I hope this gives you info on a bunch of things that would help you learn ML better.
Note: You don’t need to know all of that to learn ML. I only picked those up along the way through my studies and work. I’m only putting them here because I wanted to consciously jot down what I already know, that will help me learn faster.
That’s it for this time! My official journey begins tomorrow!