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Jeremy Howard 2020-03-03 06:47:50 -08:00
parent 32fa92891f
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01_intro.ipynb
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@ -2195,7 +2195,7 @@
"\n",
"Except when we mention it explicitly, 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. Click on the \"Cell\" menu and then on \"Run All Above\" to run all cells above the point where 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. Click on the \"Cell\" menu and then on \"Run All Above\" to run all cells above the point where you are. We have found this to be very useful when developing the fastai library."
]
},
{

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21_learner.ipynb
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"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 are 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!"
]
},
{