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Many #machinelearning algorithms, whether supervised or unsupervised, make use of distance measures.
Take k-NN for example, a technique often used for supervised learning. As a default, it often uses euclidean distance.
By itself, a great distance measure.
Knowing when to use which distance measure can help you go from a poor classifier to an accurate model.
Study: https://towardsdatascience.com/9-distance-measures-in-data-science-918109d069fa
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I honestly don't think the pay is even all that great? I'm thinking of switching to tech if possible
Our company invites most all creatives in for pitches pretty often. Helps exercise our creative muscles and keep morale up.
Sounds like y’all may have it worked out to where it’s not an added weight on top of pharma day-to-day but I could see this being a morale killer if it wasn’t implemented just so.
I do notice that when I’ve been pulverized on dry accounts for a while I am so much sharper when I get a fun assignment elsewhere.
It's honestly exhausting sometimes. I have really considered switching industries.
I feel like I have to do mental gymnastics to work at all. Hoenstly I am so burnt out.
What are the challenges in pharma?
Also the mental gymnastics legal reviewers go through thinking about how a claim can possibly be misconstrued in a way that means the opposite of what it is saying, and then striking it in case some doctor somewhere thinks it means something it explicity doesn't.
As a PM the pay isn’t great in the pharma world and we always get the short end of the stick. I’m so desperately trying to find a way out because it drains so much out of me. And the excuse of “we’re helping people” doesn’t help me either because all I see myself doing is helping SLT make more money while day to day people aren’t getting raises