Update deploy-scikit-learn.ipynb

strata-sj-2016/ml-in-production/deploy-scikit-learn.ipynb

@@ -73,7 +73,7 @@
    "source": [
     "We can expose the trained model as a REST endpoint. This will allow other applications to consume the predictions from the model.  \n",
     "\n",
-    "In order to do that, we wrap the model object in a Python function and add it to the Predictive Service. In the function you may add your own logic for transform input to the model, ensemble different models or manipulate output before returning. Checkout out [user guide](http://turi.com/learn/userguide/#Deployment) for more details.\n",
+    "In order to do that, we wrap the model object in a Python function and add it to the Predictive Service. In the function you may add your own logic for transform input to the model, ensemble different models or manipulate output before returning. Checkout out [user guide](https://turi.com/learn/userguide/#Deployment) for more details.\n",
     "\n",
     "The result of the function needs to be  a **JSON serializable** object."
    ]