When you're evaluating a language for your next project, few things are more important than available third-party libraries and the package manager that ties them together. While early versions of Go lacked a package manager, they've made up for lost time. In this article, Ayooluwa Isaiah introduces us to go's module ecosystem to help us decide if go is "a go" for our next project.

Developers make fun of legacy systems because we're scared of them. We're afraid that the tiniest change will cause the app to break in unexpected ways. We're afraid we won't realize it until a customer complains. One way to combat this fear is through testing. In this article, José Manuel shows us how to retrofit legacy systems with acceptance test suites so we can maintain them with less fear and more confidence.

If you are a software engineer, there's a good chance that deep learning will inevitably become part of your job in the future. Even if you're not building the models that directly use CNNs, you might have to collaborate with data scientists or help business partners better understand what is going on under the hood. In this article, Julie Kent dives into the world of convolutional neural networks and explains it all in a not-so-scary way.

Whoever first said that "the fastest code is no code" must have really liked memoization. After all, memoization speeds up your application by running less code. In this article, Jonathan Miles introduces us to memoization. We'll learn when to use it, how to implement it in Ruby, and how to avoid common pitfalls. Buckle up!

These days fewer and fewer web developers get to specialize in a single language like Ruby. We use different tools for different jobs. In this article, Ayooluwa Isaiah argues that Go is the perfect complement to Ruby. The developer who knows both is in a great position to handle almost any back-end challenge.

We've all been there. You're clicking around your Rails application, and it just isn't as snappy as it used to be. You start searching for a quick-fix and find a lot of talk about caching. Take your existing app, add some caching, and voila, a performance boost with minimal code changes. However, it's not this simple. Like most quick fixes, caching can have long-term costs.

The world is full of linear relationships. When one apple costs $1 and two apples cost $2, it's easy to figure out the price of any number of apples. But what happens when you have 100s of data points? What if your data source is noisy? That's when it's helpful to use a technique called linear regression. In this article Julie Kent shows us how linear regression works, and walks through a practical example in Ruby.

Go has built-in features to make it easier for programmers to implement logging. Third parties have also built additional tools to make logging easier. What's the difference between them? Which should you choose? In this article Ayooluwa Isaiah describes both of these and discusses when you'd prefer one over the other.

When you deploy a new Rails app, you typically face a double-bind. If you use an easy platform like Heroku, you could create problems for yourself as your application scales. If you use a more fully-featured platform, you risk wasting time on ops that could be spent on your product. What if you could have both: an easy deployment option that is easy to scale?

If software's been eating the world for the past twenty years, it's safe to say machine learning has been eating it for the past five. But what exactly is machine learning? Why should a web developer care? This article by Julie Kent answers these questions. I don't have kids yet, but when I do, I want them to learn two things: Whether or not you believe that the singularity is near, there's no denying that the world runs on data.