This project was developed for the course of Artificial Neural Networks and Deep Learning for the MSc. in Mathematical Engineering at Politecnico di Milano, A.Y. 2022/2023.
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├── README.md
├── misc
│ ├── report_material
│ ├── submission_template
│ │ ├── metadata
│ │ ├── model.py
│ │ ├── model_aug.py
│ │ └── scaler.gz
│ └── training_histories
├── notebook
│ ├── final_model.ipynb
│ ├── utils
│ │ ├── augmentation.py
│ │ ├── datasets.py
│ │ ├── dtw.py
│ │ ├── helper.py
│ │ ├── input_data.py
│ │ ├── models.py
│ │ ├── nemenyi.py
│ │ └── prototype_selection.py
│ ├── x_train.npy
│ └── y_train.npy
├── report
│ ├── bibliography.bib
│ ├── report.pdf
│ └── report.tex
└── requirements.txt
7 directories, 49 files
final_model.ipynbis the main file that performs training of all the models and produces all the output images.report_materialandtraining_historiesare folders containing additional images, namely the plots of the different training histories of the various models.submission_templatecontains the code used to submit the model in the competition.x_train.npyandy_train.npyare the given dataset.utilscontains the code to perform data augmentation.requirements.txtcontains the necessary packages for the environment.
- Paolo Botta (@ploki99)
- Teo Bucci (@teobucci)
- Silvia Caresana (@silviacaresana)
Check out the final report.pdf.