MNIST Classification Projects for CS 480/680 Fall 2019 (UWaterloo)

Fine-tunning VGG11 model with MNIST
- Training VGG11 model with MNIST
- Inspecting the training process
  - Loss function vsepoch
  - Accuracy vs epoch
- Inspecting the generalization properties
  - Test accuracy vs the degree of rotation
  - Test accuracy vs Gaussian noise
- Data augmentation using rotation and adding Gaussian noise
  - Test accuracy vs the degree of rotation after data augmentation
  - Test accuracy vs Gaussian noise after data augmentation
Bayes Gaussian Mixture Models (GMM)
- Fitting Data set into K Gaussian Models
- Inspecting impact of PCA

Name		Name	Last commit message	Last commit date
Latest commit History 13 Commits
CNN(Part1).ipynb		CNN(Part1).ipynb
CNN(Part2).ipynb		CNN(Part2).ipynb
CNN(Part3).ipynb		CNN(Part3).ipynb
EM_GMM.ipynb		EM_GMM.ipynb
README.md		README.md
accuracy.png		accuracy.png
loss.png		loss.png
model.png		model.png
noise.png		noise.png
noise_aug.png		noise_aug.png
pca.png		pca.png
rotation.png		rotation.png
rotation_aug.png		rotation_aug.png

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