Update a link in the autograd_tutorial.py

beginner_source/blitz/autograd_tutorial.py

@@ -67,7 +67,7 @@
 loss.backward() # backward pass
 
 ############################################################
-# Next, we load an optimizer, in this case SGD with a learning rate of 0.01 and `momentum <https://towardsdatascience.com/stochastic-gradient-descent-with-momentum-a84097641a5d>`__ of 0.9.
+# Next, we load an optimizer, in this case SGD with a learning rate of 0.01 and `momentum <https://medium.com/data-science/stochastic-gradient-descent-with-momentum-a84097641a5d>`__ of 0.9.
 # We register all the parameters of the model in the optimizer.
 #