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NNIBasedOptimisation
NNIBasedOptimisation
 
 
plots
plots
 
 
test
test
 
 
tobi
tobi
 
 
tune
tune
 
 
.DS_Store
.DS_Store
 
 
.gitignore
.gitignore
 
 
AI_Grid_Hackathon.ipynb
AI_Grid_Hackathon.ipynb
 
 
AI_Grid_Hackathon_JB_DEV.ipynb
AI_Grid_Hackathon_JB_DEV.ipynb
 
 
AI_Grid_Hackathon_JP_DEV.ipynb
AI_Grid_Hackathon_JP_DEV.ipynb
 
 
AI_Grid_Hackathon_SO.ipynb
AI_Grid_Hackathon_SO.ipynb
 
 
AI_Grid_Hackathon_large_Search.ipynb
AI_Grid_Hackathon_large_Search.ipynb
 
 
AI_Grid_Hackathon_vk.ipynb
AI_Grid_Hackathon_vk.ipynb
 
 
LSTM_500LB_Dropout_160D16_20E_20Epochs_2Inp.h5
LSTM_500LB_Dropout_160D16_20E_20Epochs_2Inp.h5
 
 
LoadProfile_20IPs_2016.csv
LoadProfile_20IPs_2016.csv
 
 
LoadProfile_30IPs_2017.csv
LoadProfile_30IPs_2017.csv
 
 
forecasts_2016.csv
forecasts_2016.csv
 
 
forecasts_2017.csv
forecasts_2017.csv
 
 
holidays_2016.json
holidays_2016.json
 
 
holidays_2017.json
holidays_2017.json
 
 
plot.py
plot.py
 
 
requirements.txt
requirements.txt
 
 
results_2016_autogluon.json
results_2016_autogluon.json
 
 
results_2017_autogluon.json
results_2017_autogluon.json
 
 
results_peak_2016_autogluon.json
results_peak_2016_autogluon.json
 
 
results_peak_2017_autogluon.json
results_peak_2017_autogluon.json
 
 
run.py
run.py
 
 
simple_eval.ipynb
simple_eval.ipynb
 
 
test_run_3773878.err
test_run_3773878.err
 
 
test_run_3773878.out
test_run_3773878.out
 
 
train.sh
train.sh
 
 
training_process_2016_14.csv
training_process_2016_14.csv
 
 
training_process_2016_15.csv
training_process_2016_15.csv
 
 
training_process_2016_16.csv
training_process_2016_16.csv
 
 
training_process_2016_17.csv
training_process_2016_17.csv
 
 
training_process_2016_18.csv
training_process_2016_18.csv
 
 
training_process_2016_19.csv
training_process_2016_19.csv
 
 
training_process_2016_20.csv
training_process_2016_20.csv
 
 
training_process_2017_23.csv
training_process_2017_23.csv
 
 
training_process_2017_24.csv
training_process_2017_24.csv
 
 
training_process_2017_25.csv
training_process_2017_25.csv
 
 
training_process_2017_26.csv
training_process_2017_26.csv
 
 
training_process_2017_27.csv
training_process_2017_27.csv
 
 
training_process_2017_28.csv
training_process_2017_28.csv
 
 
training_process_2017_29.csv
training_process_2017_29.csv
 
 
training_process_2017_30.csv
training_process_2017_30.csv
 
 

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Forecasting of Energy Loads of small and medium sized enterprises in Germany, as Part of the AIGrid Hackathon 24

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