diff --git a/ML_Algorithms/Logistic_Regression/logistic_regression.py b/ML_Algorithms/Logistic_Regression/logistic_regression.py
new file mode 100644
index 0000000..3b1aff6
--- /dev/null
+++ b/ML_Algorithms/Logistic_Regression/logistic_regression.py
@@ -0,0 +1,46 @@
+import math
+
+class logisticRegression():
+
+    def __init__(self,points):
+        self.points=points
+
+    def sigmoid(self,x,w,b):
+        z = float(x)*float(w) + float(b)
+        h = 1.0 / (1.0 + math.exp((-1.0 * z)))
+        return h
+
+    def grad_descent(self,epochs,w,b):
+        for i in range(epochs):
+            del_w = 0.0
+            del_b = 0.0
+            m = len(self.points)
+            for j in range(len(self.points)):
+                h = self.sigmoid(self.points[j][0],w,b)
+                del_w = del_w + (float(self.points[j][0])*(float(h) - float(self.points[j][1])))
+                del_b = del_b + (float(h) - float(self.points[j][1]))
+            del_w = del_w / float(m)
+            del_b = del_b / float(m)
+            w = w - 0.1*float(del_w)
+            b = b - 0.1*float(del_b)
+        return w,b
+    
+    def visualizer(self):
+        w = 1
+        b = 0
+        arr = [[0 for i in range(2)] for j in range(6)]
+        arr[0][0] = w
+        arr[0][1] = b
+        for i in range(4):
+            w,b = self.grad_descent(4,w,b)
+            arr[i+1][0] = w
+            arr[i+1][1] = b
+        w,b = self.grad_descent(1000,w,b)
+        arr[5][0] = w
+        arr[5][1] = b
+        return arr
+
+
+            
+
+