diff --git a/QA with Tensorflow.ipynb b/QA with Tensorflow.ipynb
index 0f7c048..dc71e03 100644
--- a/QA with Tensorflow.ipynb	
+++ b/QA with Tensorflow.ipynb	
@@ -21,7 +21,7 @@
     "- [Numpy](http://www.numpy.org)\n",
     "- [Matplotlib](http://matplotlib.org)\n",
     "\n",
-    "Optionally, you can install TQDM to view training progess and get training speed metrics, but it's not required. The code and Jupyter Notebook for this article is [on GitHub](https://github.com/Steven-Hewitt/QA-with-Tensorflow), and I encourage you to grab it and follow along. If this is your first time working with TensorFlow, I recommend that you first check out Aaron Schumacher's [\"Hello, TensorFlow\"](https://www.oreilly.com/learning/hello-tensorflow) for a quick overview of what TensorFlow is and how it works. If this is your first time using TensorFlow for natural language tasks, I would also encourage you to check out [\"Textual Entailment with TensorFlow\"](#link not live yet), as it introduces several concepts that will be used to help construct this network.\n",
+    "Optionally, you can install TQDM to view training progess and get training speed metrics, but it's not required. The code and Jupyter Notebook for this article is [on GitHub](https://github.com/Steven-Hewitt/QA-with-Tensorflow), and I encourage you to grab it and follow along. If this is your first time working with TensorFlow, I recommend that you first check out Aaron Schumacher's [\"Hello, TensorFlow\"](https://www.oreilly.com/learning/hello-tensorflow) for a quick overview of what TensorFlow is and how it works. If this is your first time using TensorFlow for natural language tasks, I would also encourage you to check out [\"Textual Entailment with TensorFlow\"](https://www.oreilly.com/learning/textual-entailment-with-tensorflow), as it introduces several concepts that will be used to help construct this network.\n",
     "\n",
     "Let's start by importing all of the relevant libraries:"
    ]