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It seems these days like programming with dependent types in Haskell (and its advantages) is moving slowly but steadily to the mainstream of Haskell programming. In the current state of Haskell education, dependent types are often considered topics for advanced Haskell users. However, I can foresee a day where the ease of use of modern Haskell libraries relying on dependent types forces programming with dependent types to be an integral part of normal intermediate (or even beginner) Haskell education. There are more and more and more and more great resources and tutorials and introductions to integrating dependent types into your Haskell every day. The point of this series is to show more some practical examples of using dependent types in guiding your programming, and to also walk through the why and high-level philosophy of the way you structure your Haskell programs. It’ll also hopefully instill an intuition of a dependently typed work flow of exploring how dependent types can help your current programs. The intended audience of this post is for intermediate Haskell programmers in general, with no required knowledge of dependently typed programming. I should also point out that I’m no expert — I’m still in the process of learning this all, myself :) The first project in this series will build up to a type-safe artificial neural network implementation with back-propagation training.

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