CNN-Hyperparameter-optimization

Designing, training and optimizing MLP NN

This project is an assignment made in the context of my Master studies

Technologies

• Python
• Pytorch
• Numpy
• Matplolib
• Pandas
• Google colab

Dataset

Fashion-MNIST dataset (source : https://github.com/zalandoresearch/fashion-mnist)

• 10 clothes' categories
• Training set : 55000 images
• Validation set : 5000
• Test set : 1000

Roadmap

1. Data preprocessing
2. Data augmentation
3. Make the NN flexible to efficiently swipe hyper parameters
4. Searching for the best Hyper-parameters
   • Preprocess Wandb
   • Run four times Wandb. At each run, re adjust Hyper-parameters according to last run results
5. Evaluate the final model