How to self-study machine learning when the topics get too complex as a beginner
Sometimes my brain is very fast — and I feel like a genius. But sometimes this brain’s inability to grasp even the most basic concepts leaves me crying.
As I made my self - study journey to becoming an ML engineer I encountered quite a few such moments. Don't get me wrong, I love the field — and I have never felt more fulfilled like I am right now studying and working more in it. But sometimes concepts can get too complex for rookies like us. Cue moments where the brain totally gives up and refuses to comprehend anything — even if you prod it with a (metaphorical) stick.
But time is limited, and regardless of whether this brain wants or not we need to study and move along the syllabus. So I came up with ways to make learning more interesting and engaging — particularly with the more complex topics. As funny as it sounds, I started using a lot of pictures. And I started keeping two sets of definitions/ explanations for these concepts. First set was the general technical explanation. And the second set would be a simple explanation with examples like how I would explain the concept to a 5 year old. And viola — despite the childishness my brain loved it and lapped it all up.
Another note is this can be used for literally any field — provided you have the patience to go through each concept and craft a narrative. It is extra work yes — but doing this extra work also helps your brain familiarise itself with the concept, break it down and actually make sense of it in words that you will definitely understand.
So go ahead and add a bit of Disney rizz to those pages and pages of math and stats and codes to make them easier to understand.
I have a series coming up where I share a few of these. The first part is about encoding and choosing the best encoders — find it here!