Deep Learning Notebooks

Here are my jupyter notebooks on deep learning. All of them are written in pytorch and most of them use the fastai library.

Tutorials

The rest is just a bun of random stuff shared with fellow fastai students.

Name		Name	Last commit message	Last commit date
Latest commit History 43 Commits
Adam and weight decay		Adam and weight decay
Experiments		Experiments
Lesson 9 loss function		Lesson 9 loss function
img		img
mAP		mAP
Bug with frozen LSTM layer.ipynb		Bug with frozen LSTM layer.ipynb
Building a French LM.ipynb		Building a French LM.ipynb
Cache pointer.ipynb		Cache pointer.ipynb
Cyclical LR and momentums.ipynb		Cyclical LR and momentums.ipynb
DeepPainterlyHarmonization.ipynb		DeepPainterlyHarmonization.ipynb
First neural net in pytorch.ipynb		First neural net in pytorch.ipynb
Initialize the bias in the final layer of an SSD.ipynb		Initialize the bias in the final layer of an SSD.ipynb
LM_wikitext.ipynb		LM_wikitext.ipynb
LM_wikitext_MOTAS.ipynb		LM_wikitext_MOTAS.ipynb
LM_wikitext_mixup.ipynb		LM_wikitext_mixup.ipynb
Learning rate finder.ipynb		Learning rate finder.ipynb
README.md		README.md
Resnet 50 and Darknet 53.ipynb		Resnet 50 and Darknet 53.ipynb
Retina net Pascal.ipynb		Retina net Pascal.ipynb
Retina net Pascal1.ipynb		Retina net Pascal1.ipynb
Understanding the new fastai API for scheduling training.ipynb		Understanding the new fastai API for scheduling training.ipynb
Using the callback system in fastai.ipynb		Using the callback system in fastai.ipynb
wikitext_103.ipynb		wikitext_103.ipynb