added gradient descent calculator

Author: divyanshugit

gradient_descent.py

@@ -0,0 +1,31 @@
+from numpy import asarray
+from numpy.random import rand
+
+# objective function
+def objective(x):
+	return x**2.0
+
+def derivative(x):
+	return x * 2.0
+
+def gradient_descent(objective, derivative, bounds, n_iter, step_size):
+	solution = bounds[:, 0] + rand(len(bounds)) * (bounds[:, 1] - bounds[:, 0])
+	for i in range(n_iter):
+		# calculate gradient
+		gradient = derivative(solution)
+		# take a step
+		solution = solution - step_size * gradient
+		# evaluate candidate point
+		solution_eval = objective(solution)
+		# report progress
+		print('>%d f(%s) = %.5f' % (i, solution, solution_eval))
+	return [solution, solution_eval]
+
+# Driver Code:
+
+bounds = asarray([[-1.0, 1.0]])
+n_iter = 30
+step_size = 0.1
+best, score = gradient_descent(objective, derivative, bounds, n_iter, step_size)
+print('Done!')
+print('f(%s) = %f' % (best, score))