Effective Data Science Presentations

That is basically the opposite of what you’d want to do when presenting to a non-technical audience.If your audience is full of a bunch of STEM PhD’s then have at it, but in many instances we need to adjust the way we think about presenting our technical material.I could go on and on forever about this topic, but here we’ll cover:Talking about model output without talking about the modelPainting the picture using actual customers or inputsPutting in the Time to Tell the StoryTalking about model output without talking about the modelCertain models really lend themselves well to this..You want to tell the story and log odds certainly are not going to tell the story for your stakeholders.A good first step for a logistic regression model would just be to exponentiate the log odds so that you’re at least dealing in terms of odds..Since this output is multiplicative, you can say:“For each unit increase of [variable] we expect to see a lift of x% on average with everything else held constant.”So instead of talking about technical aspects of the model, we’re just talking about how the different drivers effect the output..Choose a couple people with a high probability of churning, and a couple with a low probability of churning and talk about those people.“Mary here has been a customer for a long time, but she has been less engaged recently and hasn’t done x, y, or z (model drivers), so the probability of her cancelling her subscription is high, even though customers with longer tenure are usually less likely to leave.”Putting in the Time to Tell the StoryAs stated before, it takes some extra work to put these things together. Another great example is in cluster analysis. You could create a slide for each attribute, but then people would need to comb through multiple slides to figure out WHO cluster 1 really is vs. cluster 2, etc. You want to aggregate all of this information for your consumer. And I’m not above coming up with cheesy names for my segments, it just comes with the territory :).It’s worth noting here that if I didn’t aggregate all this information by cluster, I also wouldn’t be able to speak at a high level about who was actually getting into these different clusters..That would be a large miss on my behalf, because at the end of the day, your stakeholders want to understand the big picture of these clusters.Every analysis I present I spend time thinking about what the appropriate flow should be for the story the data can tell..And we’re not just dealing with the data that is actually in the model.. More details

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