completed part 1 of deep learning

python/Deep Learning/Introduction to Neural Networks/Softmax/cross_entropy.py

@@ -0,0 +1,10 @@
+import numpy as np
+
+# Write a function that takes as input two lists Y, P,
+# and returns the float corresponding to their cross-entropy.
+
+
+def cross_entropy(Y, P):
+    Y = np.float_(Y)
+    P = np.float_(P)
+    return -np.sum(Y * np.log(P) + (1 - Y) * np.log(1 - P))