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https://github.com/saschagrunert/nn

A tiny neural network 🧠
https://github.com/saschagrunert/nn

backpropagation backpropagation-algorithm haskell haskell-library machine-learning neural-network neural-networks

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A tiny neural network 🧠

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# ηn
## A tiny neural network 🧠

This small neural network is based on the
[backpropagation](https://en.wikipedia.org/wiki/Backpropagation) algorithm.

## Usage

A minimal usage example would look like this:

```haskell
import AI.Nn (new
,predict
,train)

main :: IO ()
main = do
{- Creates a new network with two inputs,
two hidden layers and one output -}
network <- new [2, 2, 1]

{- Train the network for a common logical AND,
until the maximum error of 0.01 is reached -}
let trainedNetwork = train 0.01 network [([0, 0], [0])
,([0, 1], [0])
,([1, 0], [0])
,([1, 1], [1])]

{- Predict the learned values -}
let r00 = predict trainedNetwork [0, 0]
let r01 = predict trainedNetwork [0, 1]
let r10 = predict trainedNetwork [1, 0]
let r11 = predict trainedNetwork [1, 1]

{- Print the results -}
putStrLn $ printf "0 0 -> %.2f" (head r00)
putStrLn $ printf "0 1 -> %.2f" (head r01)
putStrLn $ printf "1 0 -> %.2f" (head r10)
putStrLn $ printf "1 1 -> %.2f" (head r11)
```

The result should be something like:

```console
0 0 -> -0.02
0 1 -> -0.02
1 0 -> -0.01
1 1 -> 1.00
```

## Hacking
To start hacking simply clone this repository and make sure that
[stack](https://docs.haskellstack.org/en/stable/README/) is installed. Then
simply hack around and build the project with:

```console
> stack build --file-watch
```

## Contributing
You want to contribute to this project? Wow, thanks! So please just fork it and
send me a pull request.