corrections

01_intro.ipynb

@@ -140,7 +140,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The realised that a simplified model of a real neuron could be represented using simple addition and thresholdingas shown in <<neuron>>. Pitts was self-taught, and, by age 12, had received an offer to study at Cambridge with the great Bertrand Russell. He did not take up this invitation, and indeed throughout his life did not accept any offers of advanced degrees or positions of authority. Most of his famous work was done whilst he was homeless. Despite his lack of an officially recognized position, and increasing social isolation, his work with McCulloch was influential, and was picked up by a psychologist named Frank Rosenblatt."
+    "They realised that a simplified model of a real neuron could be represented using simple addition and thresholdingas shown in <<neuron>>. Pitts was self-taught, and, by age 12, had received an offer to study at Cambridge with the great Bertrand Russell. He did not take up this invitation, and indeed throughout his life did not accept any offers of advanced degrees or positions of authority. Most of his famous work was done whilst he was homeless. Despite his lack of an officially recognized position, and increasing social isolation, his work with McCulloch was influential, and was picked up by a psychologist named Frank Rosenblatt."
    ]
   },
   {
@@ -1276,7 +1276,7 @@
     "- The functional form of the *model* is called its *architecture* ;\n",
     "- The *weights* are called *parameters* ;\n",
     "- The *results* of the model are called *predictions* ;\n",
-    "- The measure of *performance* is called the *loss* (or *cost* or *error*);\n",
+    "- The measure of *performance* is called the *loss*;\n",
     "- The loss depends not only on the predictions, but also the correct *labels* (or *targets*), e.g. \"dog\" or \"cat\".\n",
     "\n",
     "After making these changes, our diagram in <<training_loop>> looks like this:"
@@ -2172,7 +2172,7 @@
     "\n",
     "Except when we mention it explicitely, the notebooks provided on the book website are meant to be run in order, from top to bottom. In general, when experimenting, you will find yourself executing cells in any order to go fast (which is a super neat feature of Jupyter Notebooks) but once you have explored and arrive at the final version of your code, make sure you can run the cells of your notebooks in order (your future self won't necessarily remember the convoluted path you took otherwise!). \n",
     "\n",
-    "In edit mode, pressing `0` twice will restart the *kernel* (which is the engine powering your notebook). This will wipe your state clean and make it as if you had just started in the notebook. Clean then on the \"Cell\" menu and then on \"Run All Above\" to run all the cells above the point you are. We have found this to be very useful when developing the fastai library."
+    "In command mode, pressing `0` twice will restart the *kernel* (which is the engine powering your notebook). This will wipe your state clean and make it as if you had just started in the notebook. Clean then on the \"Cell\" menu and then on \"Run All Above\" to run all the cells above the point you are. We have found this to be very useful when developing the fastai library."
    ]
   },
   {
@@ -2880,7 +2880,10 @@
   },
   "toc": {
    "base_numbering": 1,
-   "nav_menu": {},
+   "nav_menu": {
+    "height": "410px",
+    "width": "290px"
+   },
    "number_sections": false,
    "sideBar": true,
    "skip_h1_title": true,

02_production.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -688,7 +688,7 @@
     "item_tfms=Resize(128)\n",
     "```\n",
     "\n",
-    "Our images are all different sizes, and this is a problem for deep learning: we don't feed the model one image at a time but several (what we call a *mini-batch*) of them. To group them in a big array (usually called *tensor*) that is going to go through our model, they all need to be of the same size. So we need to add a transform twhich will resize these images to the same size. *item transforms* are pieces of code which run on each individual item, whether it be an image, category, or so forth. fastai includes many predefined transforms; we will use the `Resize` transform here.\n",
+    "Our images are all different sizes, and this is a problem for deep learning: we don't feed the model one image at a time but several (what we call a *mini-batch*) of them. To group them in a big array (usually called *tensor*) that is going to go through our model, they all need to be of the same size. So we need to add a transform which will resize these images to the same size. *item transforms* are pieces of code which run on each individual item, whether it be an image, category, or so forth. fastai includes many predefined transforms; we will use the `Resize` transform here.\n",
     "\n",
     "This command has given us a `DataBlock` object. This is like a *template* for creating a `DataLoaders`. We still need to tell fastai the actual source of our data — in this case, the path where the images can be found."
    ]

21_learner.ipynb

@@ -23,7 +23,7 @@
    "source": [
     "This final chapter (other than the conclusion, and the online chapters) is going to look a bit different. We will have far more code, and far less pros than previous chapters. We will introduce new Python keywords and libraries without discussing them. This chapter is meant to be the start of a significant research project for you. You see, we are going to implement all of the key pieces of the fastai and PyTorch APIs from scratch, building on nothing other than the components that we developed in <<chapter_foundations>>! The key goal here is to end up with our own `Learner` class, and some callbacks--enough to be able to train a model on Imagenette, including examples of each of the key techniques we've studied. On the way to building Learner, we will be creating Module, Parameter, and even our own parallel DataLoader… and much more.\n",
     "\n",
-    "The end of chapter questionnaire is particularly important for this chapter. This is where we will be getting you started on the many interesting directions that you could take, using this chapter as your starting out point. What we really saying is: follow through with this chapter on your computer, not on paper, and do lots of experiments, web searches, and whatever else you need to understand what's going on. You've built up the skills and expertise to do this in the rest of this book, so we think you are going to go great!"
+    "The end of chapter questionnaire is particularly important for this chapter. This is where we will be getting you started on the many interesting directions that you could take, using this chapter as your starting out point. What we really are saying is: follow through with this chapter on your computer, not on paper, and do lots of experiments, web searches, and whatever else you need to understand what's going on. You've built up the skills and expertise to do this in the rest of this book, so we think you are going to go great!"
    ]
   },
   {