Partner inexplicably says you need to come off crazy book smart in this meeting, context irrelevant.
What's the fanciest analytics/stats/ML concept you can explain off the top of your head? 🎓

likefunny
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just refer to machine learning as a trained monkey, works every time

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I’d walk the client through the concept of how ensembles can improve predictive power. Start off with something they know (a decision tree) and how maths can be used to make an optimal one. Then move on to the evidence there is on how using many of these decision trees (random forest) on slightly different data (through randomisation) can help cater for the veracity there is in data / models. Possibly then you can elaborate on other successful methods that work similarly (XGB)

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Same s..t consultants were explaining to me in 2015 :) .. tell me something new

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Microsoft PowerBI is made by Microsoft

likefunny

Oh I should change that to Accenture now lol, thanks for the reminder

Just say Bayesian a lot

likefunny

Prior beliefs and updated beliefs

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Just wear glasses to the meeting. The internet tells me people will think you’re smarter.

likefunny

Then have a coworker yell in the background as you slow-mo take them off every time there's an opportunity for a pun

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2 words...posed in a way that is half question, half propsal...

ENSEMBLE MODEL?!

likesmartfunny

Deep reinforcement learning with a great video that shows learning progress. You could even do a hand-calculated example on a whiteboard if you want.

A live demo of DALLE-2 and/or GPT-3 and/or sonantic for context, or something else close to whatever context your audience might best relate to.

smartlike

Huh. Didn't know Lighthouse went this hard. 👏

I've even done some deep RL research before, but hell if I can remember how any of it works now besides drawing the basic agent-environment loop picture

likehelpful

That’s why no one trusts the big 4 for any tech engagement. They make very little effort on actually getting good talent.

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They do but talent does not stay around due to projects being non engaging most of the time .. unless you are part of the lower charging offshore or nearshore team

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Hierarchical Linear Modeling is about all I got

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Like KPMG2 said, make it Bayesian and you're in business lol

likefunny

Star and snowflake schemas

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Inverse probability treatment weighting applied to propensity scores and then used to run a piecewise cox proportional hazards model with time interactions. 🤓

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I prefer logistic hazards for greater flexibility. But I guess some people prefer a rigid Cox

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I usually talk about getting from MLOps lvl 1 to MLOps lvl 2.

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ML ops is like agile though now. Try harder

General overview about how a transformer architecture works

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I spend half my time trying to make things sound simple and easy.

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Moving from traditional segmentation and modeling to network analysis. Leveraging the direction of movement along the edges to further separate customers into desired behavior and concentrating model development on improvement along the largest pools in the worst directions.

It's the back of the napkin visual and the quick transfer of knowledge of a whole host of concepts that pretty much has them filling in the nodes and doing huge chunks of my work for me... if we have to decend into anything it's usually intro to graph.

smart

Am I wrong in saying you could talk about genetic algorithms in code?
Reward good behavior, punish bad?

Disclaimer - not my field of expertise

The Monte Carlo algorithm for predictive analytics vs the accuracy of a dedicated algorithm

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likehelpful

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likesmart

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