Adam, in a post on Medium: This guide is for anyone who is curious about machine learning but has no idea where to start. I imagine there are a lot of people who tried reading the wikipedia article, got frustrated and gave up wishing someone would just give them a high-level explanation. That’s what this is. Machine learning is a domain I want to learn about as a hobby. If you’ve been inquisitive about Machine learning, Adam’s article is a nice resource to get a basic idea. There’s some very basic code written here. A little fact to get you interested: the iPhone 7’s camera uses machine learning when you click an image to find the best picture.
David Brooks writing in The New York Times’ Op-Ed Column: Large parts of popular culture — and pretty much all of stand-up comedy — consist of reducing people to one or another identity and then making jokes about that generalization. The people who worry about cultural appropriation reduce people to an ethnic category and argue that those outside can never understand it. A single identity walls off empathy and the imagination. We’re even seeing a wave of voluntary reductionism. People feel besieged, or they’re intellectually lazy, so they reduce themselves to one category. And: The only way out of this mess is to continually remind ourselves that each human is a conglomeration of identities: ethnic, racial, professional, geographic, religious and so on. Even each identity itself is not one thing but a tradition of debate about the meaning of that identity. Furthermore, the dignity of each person is not found in the racial or ethnic category that each has inherited, but in the moral commitments that each individual has chosen and lived out. Not thinking of people’s choices, characters, likes and dislikes as a binary ‘this-or-that’ is one of the most important things I’ve learned and I wanted to share with you this article (as I struggle to find time to write more often) since it’s a big step along this line of thought. I think this form of either-this-or-that classification exists so much in the tech world too—you’re either among the tech-elite or not1. I’m guilty of writing writing this way too and I’d like to change that. Sure, a common agreement could be that a person can lie somewhere in the middle, be a combination of the two extremes but that still seems like a disservice to our complex and diverse nature. You could be part tech-savvy and part not, but you are also part woman, man, grown-up, childlike, smart, foolish, extroverted, introverted etc. and I think those parts of you add-up and influence your decisions more than an aggregated summary of you would suggest. While it stands to reason that in writing about technology2 it seems convenient to refer to people as ‘tech-people’ or ‘non-tech-people’, I hope that practice doesn’t carry into our understanding of those people. I’ve heard the phrase ‘technologically-challenged’ thrown around constantly. ↩︎ Or any other category—the original NYT story is about the American elections and how the pollsters were way off-mark. ↩︎