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Modern Research: Faster Is Different

Faster is different. It sounds strange at first because we expect faster to be better. We expect faster to be more. If we can analyze data faster, we can analyze more data. If we can network faster, we can network with more people. Faster is more, which is better, but more is different.

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Owning the full-stack: A homesteading analogy on software, innovation, and freedom

Have you ever met a homesteader who owns a mansion? Me either. My neighbor, Bill (80), is a homesteader who tries to be as self sufficient as possible. From what I can see, it’s an immensely rewarding and humble existence. Life-satisfaction oozes out of his every pore and, eventually, even enduring the hardships must have become rewarding to him.

He was wearing an interesting smile when he told me that for 20 years the only inputs to the property were paper goods (read as: toilet paper) and that they don’t have any source of heat other than wood, which he cuts off his own property. Homesteading is immensely hard and it’s not for everyone. Homesteaders don’t have the time to live a life of luxury because homesteading means you have to own all the problems of life. The problems of food and shelter, and producing enough value to trade for things you can’t produce yourself. I think this is similar to how a full stack developer has to own the problems of the whole stack.

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Rapid Data Products: Kicking the Tires on IBM Watson in One Day

Late last year I turned the venerable age of 40, and graying and balding jokes aside, I've spent a good bit of time reflecting on the accelerating pace of change in technology. It's not just that things are getting faster, better, cheaper. It's that whole new capabilities are now possible that we could only dream about even a few decades ago. Mail is electronic. A TV and a computer are basically the same thing. And you can talk to your phone.

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A Novice Coder, a Finance Data Application, and the Value of Rapid Prototyping

I like to build things. I like analysis. I like programming. Interestingly, you often need to reverse that order before you’re in a position to build an application for analyzing something. You need programming knowledge to turn the analysis into a “thing.” The problem is, while I like programming, I’m still new to it. I mean, I’m Codecademy good, but that doesn’t translate into a user facing application leveraging Python, Javascript, and D3. So, when I recently sat down to build a minimally viable data application for looking at airline stocks, I wondered how long it might take to get to viable and, frankly, feared how minimal it might be.

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How a Data Scientist Built a Web-Based Data Application

I’m an algorithms guy. I love exploring data sets, building cool models, and finding interesting patterns that are hidden in that data. Once I have a model, then of course I want a great interactive, visual way to communicate it to anyone that will listen. When it comes to interactive visuals there is nothing better than JavaScript’s D3. It’s smooth and beautiful.

But like I said, I’m an algorithms guy. Those machine learning models I’ve tuned are in Python and R. And I don’t want to spend all my time trying to glue them together with web code that I don't understand very well and I’m not terribly interested in.

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How I Made a Neural Network Web Application in an Hour

Computer vision is an exciting and quickly growing set of data science technologies. It has a broad range of applications from industrial quality control to disease diagnosis. I have dabbled with a few different technologies that fall under this umbrella before, and I decided that it would be a worthwhile endeavor to rapid prototype an image recognition web application that used a neural network.

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