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A comment on Why is machine learning 'hard'? (2016).

Re:Why is machine learning 'hard'? (2016) by DeathArrow on Wednesday January 24, 2024 @04:48AM (#39115508)
As with everything, if you don't know the fundamentals, the basics, you are very limited on what you can achieve and find stuff difficult.

To use a parallel from software if you just know a programming language, how to call libraries and APIs you can't compare to a guy with a solid CS background who also understands algorithms, data structures, complexity, math and knows how computers work down to NAND gates.

Because I have studied some ML fundamentals during my batchelor and master degrees I know I am not competent in ML and AI. But I know how to become competent if I need or want to. Most people do believe finishing a bootcamp and calling some frameworks in Python makes them competent.

[ Parent | on HN ]
Re:Why is machine learning 'hard'? (2016) by jurgenaut23 on Wednesday January 24, 2024 @04:53AM (#39115539)
Yes, bootcamps are really a great way to score high on the Dunning-Kruger score, but not so much on any other metric of value. You need lots of sweat and tears to become a capable and competent ML engineer, especially to tell apart intrinsic limitations (i.e., no signal in your data) vs extrinsic issues (e.g., a bug anywhere between ETL and prediction, or a methodological mistake).
[ Parent | on HN ]
Re:Why is machine learning 'hard'? (2016) by kick_in_the_dor on Wednesday January 24, 2024 @09:40AM (#39117839)
> and knows how computers work down to NAND gates.

I lol'd

[ Parent | on HN ]