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notes.txt
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notes.txt
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'''
_______________________________________________
METRICS
model.py
Accuracy of the last model: ------------------------------------------------- 96.52%
Lower loss registered in epoch 2/2 step 600/600: ---------------------------- 0.0505
model_cnn.py
Accuracy of the last model: ------------------------------------------------- 96.28%
Lower loss registered in epoch 2/2 step 600/600: ---------------------------- 0.0959
model_cnn2.py
Accuracy of the last model: ------------------------------------------------- 98.19%
Lower loss registered in epoch 2/2 step 600/600: ---------------------------- 0.0392
_______________________________________________
NOTES AND LINKS FOR THE PROJECT
- Tutorial (Youtube video):
https://www.youtube.com/watch?v=bA7-DEtYCNM&t=115s
- Classification MNIST model (Github doc):
https://github.com/python-engineer/pytorchTutorial/blob/master/13_feedforward.py
- Original project (Github repo):
https://github.com/python-engineer/pytorch-examples/tree/master/pytorch-flask-deploy
- Transfer learning with MNIST database (Github repo):
https://github.com/EdenMelaku/Transfer-Learning-Pytorch-Implementation
https://towardsdatascience.com/transfer-learning-with-convolutional-neural-networks-in-pytorch-dd09190245ce
https://www.kaggle.com/tonysun94/pytorch-1-0-1-on-mnist-acc-99-8
https://www.youtube.com/watch?v=Upw4RaERZic
https://www.youtube.com/watch?v=qaDe0qQZ5AQ
- Packages imports:
https://realpython.com/absolute-vs-relative-python-imports/
- How to perform Cross Validation in Pytorch:
https://www.machinecurve.com/index.php/2021/02/03/how-to-use-k-fold-cross-validation-with-pytorch/
'''