Paul asks, “Looking back on the way you learned about AI, is there anything you wish you would’ve figured out first?”
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Machine-Generated Transcript
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.
Paul asks, looking back on the way you learned about AI, is there anything you wish you would have figured out first? Yes.
So machine learning and data science really are a blend of, of four different areas, right.
So there’s the business side, it’s the business problem, the the business strategy you’re trying to solve, there is the data engineering side, which is handling data.
Storage, being able to, to retrieve and rank an index data this that you have stored, there is the coding side, where you have to be able to read and write code in a language like R or Python, which would allow you to be effective.
And then there’s the mathematics, you know, statistics and probability side, knowing the advanced mathematics, so that you not only know what the machines are doing, but you know why, you know why certain algorithms make for better or worse fit, certain techniques make it for better or worse fit.
And when I look back, I’m self taught on a lot of this stuff.
So I have a lot of gaps.
In my knowledge, particularly on the mathematics side, I can patch gaps pretty easily on the code side, I know the business side.
I know the data engineering side fairly well actually, because I have an IT background, but my my weak spot, my blind spot really is on the mathematics side, particularly once you get into stuff like linear algebra and things like that.
Higher level mathematics, that’s when I feel the biggest gaps.
And so from a professional development perspective, certainly, that’s something I wish I had known, more of going into this.
And certainly something that I’m spending a lot of time nowadays, trying to remediate so that it’s not as big a weakness, right? It’s not as big of a gap.
do a self assessment in those four areas and figure out which area are you weakest in? Which area are you strongest in, and then try to patch those weak spots, particularly if you’re still in school.
Definitely take the time to patch those weak spots, take an extra course in something that you know you’re not good at.
So that it’s less of a vulnerability or added also it’s at the very least, you’re not going to be paying a lot of money to an institution to later on to reteach you something you have to learn the first time around.
Good question.
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