Fix formatting

exercises/01_penguin_classification.ipynb

@@ -448,7 +448,7 @@
     "### Task 9: Writing basic training and validation loops\n",
     "\n",
     "- Before we jump in and write these loops, we must first choose an activation function to apply to the model's outputs. We chose not to include this in the network itself.\n",
-    "  - We need to convert our model outputs into something that can be compared to our targets i.e. `[0,0,1]`.\n",
+    "  - We need to convert our model outputs into something that can be compared to our targets i.e. `[0, 0, 1]`.\n",
     "  - Here we are going to use the softmax activation function: see [the PyTorch docs](https://pytorch.org/docs/stable/generated/torch.nn.Softmax.html). It can be seen as a generalization of both the logits and sigmoid functions to handle multi-class classification tasks\n",
     "  - For those of you who've studied physics, you may be reminded of the partition function in thermodynamics.\n",
     "  - This activation function is good for classification when the result is one of ``A or B or C``.\n",