Training ensembles of deep learning models to understand their advantages in terms of performance.
Looking for more efficient distribution of training/computational budgets.
- scripts
- results
- datasets
main.py
Run the entire training and testing for all the models definedread_logs.py
Text to Pandas Dataframe to plot the logs of the trainingresults.py
Class Results to store the results in Dicts during trainingtrain.py
train_ensemble.py
test.py
Measure the performance of all the models in the test set