Self-taught ML/data science engineer with 5 years in industry questions if continuous learning truly pays off when knowledge retention feels logarithmic. Should I opt for ‘just in time’ learning?
Ongoing learning is beneficial despite the occasional challenge of forgetting details. In my experience, the process of learning is not solely about memorizing facts; it is also about cultivating the ability to reason and solve problems. I have found that learning in short, focused sessions followed by practical application helps solidify core concepts. Even if specific details fade, reusable techniques and frameworks remain accessible, enabling a more adaptable approach to problems. This cycle of review and practice ultimately reinforces skills over time.
i feel continuous learning is like gym for your brain - yes, you might forget bits, but the overall skill stacks up. try mixing in recap sessions and hands-on practice. it eventually kinda clicks even if you dont remember every detail
hey, i find that blending short self-reviews wit small, fun projects helps me reconnect with fading details. have u tried any creative reps to keep info alive? what little tricks work best for u?
hey, continuous learning builds up ya mind’s muscle. even if details slip away, you’re strengthening overall thinkin and problem skills. dont stress over every lost fact – it’s all a part of the learning groove.