Merge pull request #188 from J0/patch-3

Minor Typo in Chapter 11 nethod -> method

11_midlevel_data.ipynb

@@ -239,7 +239,7 @@
     "\n",
     "For each of `tok` or `num` in the preceding example, we created an object, called the `setup` method (which trains the tokenizer if needed for `tok` and creates the vocab for `num`), applied it to our raw texts (by calling the object as a function), and then finally decoded the result back to an understandable representation. These steps are needed for most data preprocessing tasks, so fastai provides a class that encapsulates them. This is the `Transform` class. Both `Tokenize` and `Numericalize` are `Transform`s.\n",
     "\n",
-    "In general, a `Transform` is an object that behaves like a function and has an optional `setup` nethod that will initialize some inner state (like the vocab inside `num`) and an optional `decode` that will reverse the function (this reversal may not be perfect, as we saw with `tok`).\n",
+    "In general, a `Transform` is an object that behaves like a function and has an optional `setup` method that will initialize some inner state (like the vocab inside `num`) and an optional `decode` that will reverse the function (this reversal may not be perfect, as we saw with `tok`).\n",
     "\n",
     "A good example of `decode` is found in the `Normalize` transform that we saw in <<chapter_sizing_and_tta>>: to be able to plot the images its `decode` method undoes the normalization (i.e., it multiplies by the standard deviation and adds back the mean). On the other hand, data augmentation transforms do not have a `decode` method, since we want to show the effects on images to make sure the data augmentation is working as we want.\n",
     "\n",