There are many good reasons to remember Tony Hsieh, but I keep thinking about one in particular: an unusual employment p

If we follow that path, then maybe we have a fighting chance as a civilization. But it will require radical change. If I say to you — how many relationships do you have with trees, you’ll look at me like I’m crazy. Am I? Then why are you so unhappy? Why do you think having relationships with fake bits of people over a smartphone is better than with real living things? Your sociality has been warped, twisted, commodified, and spat out, and you don’t even know it.

I already know what resources I plan on using when I want to dive into deep learning because I’ve had my eyes on these resources for a while. To get an intuitive understanding of neural networks, I plan on watching the first two YouTube videos. Then, I plan on going through the two courses that follow.

But if you ask me, all of us need to get as much of that as we can, as fast as we can. We were put here to love. As much of life, in all its forms, as we can hold, in the achingly brief time we have. That is what “we’re social beings” means in the most essential, simplest form.

Similar to how I started learning machine learning, I don’t know what I don’t know. Therefore, I’m going to initially be skimming through a lot of different resources. I’ll most likely be starting with Docker, as it seems to be the most widely used for deployment.

It’s becoming increasingly important that data scientists not only know how to build models but how to deploy them as well. In fact, a lot of job postings are now requiring some experience in model deployment.

But if you ask me, all of us need to get as much of that as we can, as fast as we can. We were put here to love. As much of life, in all its forms, as we can hold, in the achingly brief time we have. That is what “we’re social beings” means in the most essential, simplest form.

The reason that it’s so important to learn how to deploy models is that a model is only as valuable as its ease of use and ease of interpretability. And so, being able to deploy it in a way that anyone can interact with will be extremely useful.

I am still very much a novice in this area (I must admit!), but I believe there are several tools that can be used to deploy models like Docker, Heroku, Streamlit, and Airflow so I want to explore the different options and compare where they see fit.

Below, I’ve identified five areas that I believe will help me become ten times more valuable than right now. For each area, I’ve explained why I’ve decided to dedicate my time learning it and the resources that I plan on using to help me.

That’s the truth of us. And the sad, sad truth that Covid revealed about the West these days is that it still doesn’t get that. Does the East? A little bit more so, at least.

We were always meant to be part of all of life, as much of life as we could befriend and love and know and hold and wonder in awe at. Not just to slay each other symbolically with more money to buy more stuff with to fill the gaping hole in our souls. That hole is there in the first place because we live in denial of who we really are. Social animals, searching desperately, before our last breaths are taken, for a friend, a lover, a partner in crime.

Tony Hsieh speaks at the closing plenary session of the Clinton Global Initiative America at the Sheridan Downtown Denver, Wednesday morning, June 25, 2014. Photo: Andy Cross/The Denver Post via Getty Images

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e with a nice man and he asks me what my greatest fear is, which I guess is the kind of thing people ask on first dates. I think, and realize I know my answer: I’m scared that the children I do not yet have will die while I am still alive.

I’ve also noticed that deep learning is becoming a bigger focus throughout the community. An increasing proportion of Kaggle competitions require deep learning, more job postings require experience in deep learning, and more articles are about deep learning!

It’s increasing in relevancy. Deep learning has significantly improved over the past few years — the techniques in deep learning have been refined, the efficiency of deep learning algorithms have improved, and there’s a lot more support online around deep learning (more open source projects and more educational resources).