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Welcome to the conclusion of our series on Haskell data types! We've gone over a lot of things in this series that demonstrated Haskell's simplicity. We compared Haskell against other languages where we saw more cumbersome syntax. In this final part, we'll see...

Welcome to our Real World Haskell Series! In these tutorials, we'll explore a bunch of different libraries you can use for some important tasks in backend web development. We'll start by looking at how we store our Haskell data in databases. If you're already ...

In part 1, we began our series on production Haskell techniques by learning about Persistent. We created a schema that contained a single User type that we could store in a Postgresql database. We examined a couple functions allowing us to make SQL queries abo...

In part 1 of this series we used Persistent to store a User type in a Postgresql database. Then in part 2 we used Servant to create a very simple API that exposed this database to the outside world. This week, we're going to look at how we can improve the perf...

In first three parts of this series, we've combined several useful Haskell libraries to make a small web app. In part 1 we used Persistent to create a schema with automatic migrations for our database. Then in part 2 we used Servant to expose this database as ...

In this series so far, we've done a real whirlwind tour of Haskell libraries. We created a database schema using Persistent and used it to write basic SQL queries in a type-safe way. We saw how to expose this database via an API with Servant. We also went ahea...

AI systems are beginning to impact our lives more and more. It's a very important element to how software is being developed and will continue to be developed. But where does Haskell fit in this picture? In this series, we’ll go over the basic concepts of Tens...

I often argue that Haskell is a safe language. There are a lot of errors we will catch at compile time, rather than runtime. Runtime errors can often be catastrophic to a system, so being able to reduce these is paramount. This is especially true when programm...

In part 2 we dove into the world of dependent types. We linked tensors with their shapes at the type level. This gave our program some extra type safety and allowed us to avoid certain runtime errors. In this part, we're going to solve another runtime conundru...

In part 2 and part 3 of this series, we explored some of the most complex topics in Haskell. We examined potential runtime failures that can occur when using Tensor Flow. These included mismatched dimensions and missing placeholders. In an ideal world, we woul...

Well to our series on Haskell and the Open AI Gym! The Open AI Gym is an open source project for teaching the basics of reinforcement learning. It provides a framework for understanding how we can make agents that evolve and learn. It's written in Python, but ...

n part 1 of this series, we began our investigation into Open AI Gym. We started by using the Frozen Lake toy example to learn about environments. An environment is a basic wrapper that has a specific API for manipulating the game. Part 1's work was mostly in ...

So far in this series, the Frozen Lake example has been our basic tool. In part 2, we wrote it in Haskell. We'd like to start training agents for this game. But first, we want to make sure we're set up to generalize our idea of an environment. So in this part,...

In the last two parts of this series, we've written two simple games in Haskell: Frozen Lake and Blackjack. Now that we've written the games, it's time to explore more advanced ways to write agents for them. In this article, we'll explore the concept of Q-Lear...

In part 4 of this series, we applied the ideas of Q-learning to both of our games. You can compare the implementations by looking at the code on Github: Frozen Lake and Blackjack. At this point, we've seen enough in common with these that we can make a general...

In part 6 of the series, we used the ideas of Q-Learning together with TensorFlow. We got a more general solution to our agent that didn't need a table for every state of the game. In this part, we'll take the final step and implement this TensorFlow approach ...

Welcome to the final part of our Open AI Gym series! Throughout this series, we've explored some of the ideas in the Open AI Gym framework. We made a couple games, generalized them, and applied some machine learning techniques. When it comes to rendering our g...

Haskell is a truly awesome language for parsing. Haskell expressions tend to compose in simple ways with very clearly controlled side effects. This provides an ideal environment in which to break down parsing into simpler tasks. Thus there are many excellent p...

In part 1 of this series, we prepared ourselves for parsing by going over the basics of the Gherkin Syntax. In this part, we'll be using Regular Expression (Regex) based, applicative parsing to parse the syntax. We'll start by focusing on the fundamentals of t...

In part 2 of this series we looked at the Regex-based Applicative Parsing library. We took a lot of smaller combinators and put them together to parse our Gherkin syntax (check out part 1 for a quick refresher on that). This week, we'll look at a new library: ...