—

A Purely Functional Typed Approach to Trainable Models (Part 3)
in #differentiable programming, #deep learning, #backprop, #modeling, @Haskell, +Functional Models

—

A Purely Functional Typed Approach to Trainable Models (Part 2)
in #differentiable programming, #deep learning, #backprop, #modeling, @Haskell, +Functional Models

—

A Purely Functional Typed Approach to Trainable Models (Part 1)
in #differentiable programming, #deep learning, #backprop, #modeling, @Haskell, +Functional Models

—

Introducing the backprop library
in #functional programming, #haskell, #numerical, #artificial neural networks, @Haskell, +Backprop

—

Practical Dependent Types in Haskell 2: Existential Neural Networks and Types at
Runtime
in #functional programming, #dependent types, #numerical, #haskell, #singletons, #types, #artificial neural networks, #existential types, @Haskell, @Ramblings, +Practical Dependent Types in Haskell

—

Practical Dependent Types in Haskell: Type-Safe Neural Networks (Part 1)
in #functional programming, #dependent types, #numerical, #haskell, #singletons, #types, #linear algebra, #artificial neural networks, @Haskell, @Ramblings, +Practical Dependent Types in Haskell