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+sibe
+====
+
+A simple Machine Learning library.
+
+A simple neural network:
+```haskell
+module Main where
+  import Sibe
+  import Numeric.LinearAlgebra
+  import Data.List
+
+  main = do
+    let learning_rate = 0.5
+        (iterations, epochs) = (2, 1000)
+        a = (logistic, logistic') -- activation function and the derivative
+        rnetwork = randomNetwork 0 2 [(8, a)] (1, a) -- two inputs, 8 nodes in a single hidden layer, 1 output
+
+        inputs = [vector [0, 1], vector [1, 0], vector [1, 1], vector [0, 0]] -- training dataset
+        labels = [vector [1], vector [1], vector [0], vector [0]] -- training labels
+
+        -- initial cost using crossEntropy method
+        initial_cost = zipWith crossEntropy (map (`forward` rnetwork) inputs) labels
+
+        -- train the network
+        network = session inputs rnetwork labels learning_rate (iterations, epochs)
+
+        -- run inputs through the trained network
+        results = map (`forward` network) inputs
+
+        -- compute the new cost
+        cost = zipWith crossEntropy (map (`forward` network) inputs) labels
+```
+
+See other examples:
+```
+stack exec example-xor
+stack exec example-naivebayes-doc-classifier
+```