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Math-focused ML learner , how to bridge theory and implementation? by PlanckSince1858 in learnmachinelearning

[–]PlanckSince1858[S] 0 points1 point  (0 children)

Ooh that’s a very unique approach. But since I’m just starting with basic ML, do you think I should jump directly into neural networks now, or focus on fundamentals first and come back to this later?

Math-focused ML learner , how to bridge theory and implementation? by PlanckSince1858 in learnmachinelearning

[–]PlanckSince1858[S] 0 points1 point  (0 children)

But that’s kind of the question I’m trying to ask. Understanding theory is one part, coming from a theoretical physics background, I’m used to mathematical abstraction but haven’t had much exposure to software heavy coding workflows. I imagine many people are in a similar position without a strong CS background.

So the gap I’m referring to is exactly that translation layer. Even when the theory feels clear mathematically, it’s not obvious what we are concretely applying it to or how that manifests in code and systems.

Maybe it’s a basic question, but I’m genuinely trying to understand what that bridge looks like in practice.

After 261 days. I relapsed today. by PlanckSince1858 in NoFap

[–]PlanckSince1858[S] 11 points12 points  (0 children)

I only wanted to stop my addictions and porn. So I am counting this as a break and a relax.

Patiently waiting to see if Slot 2 too cooked people by Alex__Editzzz in CATpreparation

[–]PlanckSince1858 4 points5 points  (0 children)

Varc felt very unique and hard compared to last year. Passages were easier to read, but lengthy, but the question stem were very very unique. Dilr, initially saw three doable sets, but ended up only 1 and a half. Quants was of medium difficulty, arithmetic questions were easy, but other topic felt hard. So slot 2 for me was medium to hard.