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Zander Bailey
Zander Bailey

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Why Data Science?

Why did I decide to study Data Science? At first it bothered me that I didn't have a straightforward answer to this question, but maybe that's okay, because Data Science itself is complex. Perhaps if I just explain how I got here, all the roads that have led me to this point, it will make sense. I've studied different things, bounced around between professions, and picked up different skills along the way. I don't regret the tangents I've taken and the things I've tried. All these different experiences have given me a unique outlook. It's important to understand how my journey began in order to understand how I arrived here. So here is my story.

I like to write code. But I also want it to mean something. I've been writing code since I was a kid. Nothing fancy, just some HTML, fiddling with websites. But the foundation was there. I liked to look under the hood, so to speak, and see how programs worked. I fiddled with hex editing, tinkered with config files, and was generally curious about how the programs on my computer did what they did. So of course when I went to college, I studied theater. I graduated with a degree in lighting design, and proceeded to work in the Seattle theater scene for several years. But in the back of my mind it always bothered me a little that I hadn't taken Computer Science seriously as a career option, and I felt like I had missed my moment. At a certain point in my theater career I reached a crossroads, and I had the opportunity to go back to school. So I ended up studying computer science after all, and it was fascinating to learn the fundamentals of what makes computers tick. Although I never exactly enjoyed math classes, I don't mind doing math in the real world, in fact it's almost kind of fun, like a logic problem. After graduation I was casting about, looking for something to specialize in in an ever growing, ever evolving technical world, and I stumbled across Data Science. With its blend of coding and math, it caught my eye, and I began to read about what Data Science could accomplish. I was impressed, and I was interested to be a part of something with such an impact on so many industries, something that is still evolving and continuing to make breakthroughs.

The world of technology continues to grow and evolve, and so too must our understanding of it. Movies and video games have long been an interest of mine, and machine learning is important to to both of these areas. In video games the applications are fairly apparent: adaptive environments and npcs that change behavior based on the player's actions. In Alien: Isolation, the Alien is able to track the player and learns from their behavior, learning to hunt and stalk them. Machine learning is also responsible for being able to generate new environments and levels in a seemingly random fashion in some games. The list goes on. The film industry is also being revolutionized by AI and machine learning. In higher budget films, machine learning algorithms are able to take care of the mundane aspects of things like computer animation and special effects. It has also improved green screen mapping by leaps and bounds, like turning Josh Brolin into Thanos in real time. ML is likely to be used in the future of things like de-aging actors, as happened with Samuel L. Jackson in Captain Marvel. Similar technology is being developed for use in creating realistic, life-like characters completely from scratch, using only animation.

These are only a few of the industries where Data Science has had an impact, but there are so many ways in which Data Science and machine learning have changed aspects of our everyday lives. I find it inspiring to think about the kind of things machine learning has been able to accomplish, and it makes me wonder about what else it can help us to achieve.

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Timeless DEV post...

Git Concepts I Wish I Knew Years Ago

The most used technology by developers is not Javascript.

It's not Python or HTML.

It hardly even gets mentioned in interviews or listed as a pre-requisite for jobs.

I'm talking about Git and version control of course.

One does not simply learn git