fastai 2018 course notes
Notes for fast.ai's deep learning course, part 1, 2018 edition.
Once setup, update the OS and fastai repo:
# update the machine OS
sudo apt update
sudo apt upgrade
conda install -c conda-forge jupyterlab # install jupyterlab
# make sure the fastai git repo is up to date
git pull # run this inside the fastai folder
conda env update # updates the fastai env
conda activate fastai # activates fastai env
Lesson 1: Image classification with Convolutional Neural Networks
lr.find()
method to help find an optimal learning rate. This starts at a very low lr and keeps increasing it until the loss stops decreasing.tfms_from_model()
method, with the transformations to perform passed in with aug_tfms=
note: the fastai library is frequently updated so git pull
it from github instead of installing it using pip. to use the fastai library in my own github repo,create a symlink from the folder containing jupyter notebooks to the library like so ln -s /path/to/fastai/fastai
and import things as per the fastai notebooks.
deep learning