Follow-up

clean/01_intro.ipynb

@@ -1567,6 +1567,18 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

clean/02_production.ipynb

@@ -1080,6 +1080,18 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

clean/10_nlp.ipynb

@@ -1504,7 +1504,7 @@
     "1. What is a language model?\n",
     "1. Why is a language model considered self-supervised learning?\n",
     "1. What are self-supervised models usually used for?\n",
-    "1. What do we fine-tune language models?\n",
+    "1. Why do we fine-tune language models?\n",
     "1. What are the three steps to create a state-of-the-art text classifier?\n",
     "1. How do the 50,000 unlabeled movie reviews help create a better text classifier for the IMDb dataset?\n",
     "1. What are the three steps to prepare your data for a language model?\n",