General Question: Issue with translating learning to coding

Hi all,
I have a general question, I would love to hear if anyone has any suggestion/advice/tips
I been taking the course in the ML specialization, really loving learning ML
but one thing keeps popping up on my end, I fully understand the lecture material , however, when it comes to labs, I find myself drawing blanks for coding and wasn’t able to translate what i understand into codes

how do you get better with this? :thinking:

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It happened exactly like that to me. Many times I had to query Google for some tips. Eventually I got the gist of it. Now I can code with my eyes closed. So don’t despair and keep on going. Do your best and forget the rest!

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Do you have experience in computer programming, or in Python programming specifically?

that’s good to know!!! =) Thank you !

Yes! I have some experience in programming in python.
i guess just as the materials get a bit complex, feels a bit challenging.
Once I see hints, I can understand the code, but initially looking at the question i having a bit difficulties translate my understand to proper code! =(

I think a good hands on in python programming language, how numpy interprets matrix and vectors and its numerical operations (addition, multiplication etc.) along with continuous practice will bring what you expect. All the very best!

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Maybe one strategy you may find useful is drawing. You may create representations of what you want to do (like with boxes, circles, arrows, and how they interconnect). In doing so you may want to take really good care of indexing (like where summations start, and where the index in your arrays should start, etc. )
Then you can use those drawings as a link between the theory and the code.

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