diff --git a/ECE5930_NeuralNetworks/1-perceptron/2perc.py b/ECE5930_NeuralNetworks/1-perceptron/2perc.py
deleted file mode 100755
index 1a0ecb1..0000000
--- a/ECE5930_NeuralNetworks/1-perceptron/2perc.py
+++ /dev/null
@@ -1,57 +0,0 @@
-#!/usr/bin/env python
-
-import numpy.random as rnd
-import matplotlib.pyplot as plt
-
-def loadData(file, color):
-    dataSet = []
-    for line in open(file,"r"):
-        raw = line.split()
-        p = [1, float(raw[0]), float(raw[1])]
-        plt.scatter(p[1],p[2], 5, color, "o")
-        dataSet.append(p)
-    return dataSet
-
-def negate(set):
-    for row in set:
-        row[0] *= -1
-        row[1] *= -1
-        row[2] *= -1
-    return set
-
-def aTy(a, y):
-    sum = 0
-    for i in range(len(a)):
-        sum += a[i]*y[i]
-    return sum
-
-def gradDesc(a, rate, y):
-    for i in range(len(a)):
-        a[i] = a[i] + rate * y[i]
-    return a
-
-def main():
-    lr = 1
-    a = [rnd.random(), rnd.random(), rnd.random()]
-    set1 = loadData("perceptrondat1", "blue")
-    set2 = loadData("perceptrondat2", "red")
-
-    trainingData = set1 + negate(set2)
-
-    aOld = [0, 0, 0]
-    while aOld != a:
-        aOld = a
-        for i in range(len(trainingData)):
-            result = aTy(a, trainingData[i]) 
-            if result < 0:
-                a = gradDesc(a, lr, trainingData[i])
-
-    m = a[0]/a[1]
-    b = a[2]/a[1]
-    print("Line: y = -" + str(m) + " x - " + str(b))
-
-
-    plt.plot([-1,-1], [1,1], 'k-')
-    plt.show()
-
-main()