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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 fr
by DeathArrow 3y ago
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.
- jurgenaut23 3y agoYes, 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).
- kick_in_the_dor 3y ago> and knows how computers work down to NAND gates. I lol'd