Five things I wish people knew about real-life machine learning

Deena Gergis is a data science lead at Bayer. I recently discovered Deena’s article on LinkedIn titled “Five Things I Wish I Knew About Real-Life AI.” I think that this article is a great piece of a career advice for all the current and aspiring data scientists, as well as for all the professionals who work with them. Let’ me take Deena’s headings and add my 2 cents.

One. It is all about the delivered value, not the method.

I fully agree with this one. Nobody cares whether you used a linear regression or recurrent neural network. Nobody really cares about p-values or r-squared. What people need are results, insights, or working products. Simple, right?

Two. Packaging does matter

Again, well said. The way you present your solution to your colleagues, customers, or stakeholders can determine whether your project will get more funds and resources or not. 

Three. Doing the right things != doing things right.

Exactly. Citing Deena: “you might be perfectly predicting a KPI that no one cares about.” Enough said. 

Four. Set realistic expectations.

Not everybody realizes that “machine learning” and “artificial intelligence” are not a synonym of “magic” but rather a form of statistics (I hope “real” statisticians won’t get mad at me here). The principle “garbage in – garbage out” holds in machine learning. Moreover, sometimes, ML systems amplify the garbage, resulting in “garbage in, tons of garbage out”. 

Five. Keep humans in the loop.

Let me cite Deena again: “My customers are my partners, not just end-users.” Note that by “customers,” we don’t only mean walk-in clients, but also any internal customer, project manager, even a colleague who works on the same project. They are all partners with unique insights, domain knowledge, and experience. Use them to make your work better. 

Read the original article here. Deena Gergis has several more articles on LinkedIn here. And if you know Arabic, you might want to watch Deena’s videos on YouTube here. Unfortunately, my Arabic is not good enough to understand her Egyptian accent, but I suspect that her videos are as good as her writings.

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