Hey everyone, I've recently jumped into the world of Machine Learning. I have a decent grasp of Python and some math skills, but I'm starting to feel like I'm stuck in a loop. It seems like all I'm doing is loading data, cleaning it up, preparing it, then just calling the algorithm's class, followed by .fit and .predict. Is this really all there is to machine learning? I feel like there's got to be more depth to it. Any tips to get me out of this rut?
1 Answer
If you're looking to get a better handle on the math behind ML, I'd recommend checking out 3b1b’s series on neural networks, especially the first few videos. They really break things down nicely! Once you have that foundation, try building a simple framework from scratch. That way, you won’t be just calling .fit() and .predict() without understanding the mechanics behind it.
Totally agree! StatQuest is another awesome resource for grasping the fundamental stats and math involved in ML. Highly recommend checking it out!