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.github/CODEOWNERS

@@ -1,3 +1,34 @@
 # Codeowners for these exercise files:
 # * (asterisk) denotes "all files and folders"
 # Example: * @producer @instructor
+import numpy as np
+class perceptron:
+
+  def __init(self, inputs, bias=1.0):
+        self.weights = (np.random.rand(inputs+1)*2)-1
+        self.bias = bias
+        print(self.weights)
+
+  def run(self,x):
+    n=len(x)
+    output=0
+    for i in range(n):
+      output+=x[i] * weights[i]+bias * weights[-1]
+
+    x_sum = np.dot(np.append(x,bias),weights)
+    return sigmoid(x_sum)
+
+  def sigmoid(self, x):
+    return 1/(1+np.exp(-x))
+
+  def set_weights(self,w_init):
+    self.weights = np.array(w_init)
+
+  run([0,10])
+
+
+
+
+
+
+