rene/ma_cisco_malware
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rene 9ce11e4db4 refactor test function according to the new training procedure
2017-11-09 13:12:50 +01:00
data
refactoring and adding standard files for .gitignore and .keep in data
2017-06-30 09:04:24 +02:00
models
remove identical parameter from data loading function; add runs argument
2017-11-07 20:47:41 +01:00
scripts
remove model selection based on validation loss
2017-09-16 15:25:34 +02:00
.gitignore
add visualization for training curves, pr, roc
2017-07-14 14:58:17 +02:00
arguments.py
add parameter for hyper band iteration, use hyperband results in new runs
2017-11-08 11:09:56 +01:00
dataset.py
remove identical parameter from data loading function; add runs argument
2017-11-07 20:47:41 +01:00
fancy.sh
refactor hyperband; fix domain generation
2017-11-04 12:47:08 +01:00
hyperband.py
move model creation back into models package
2017-11-07 20:09:20 +01:00
main.py
refactor test function according to the new training procedure
2017-11-09 13:12:50 +01:00
Makefile
remove identical parameter from data loading function; add runs argument
2017-11-07 20:47:41 +01:00
README.md
Init repo
2017-06-27 20:01:09 +02:00
rerun_models.sh
refactor hyperband implementation
2017-09-29 22:59:57 +02:00
run_model_rene.sh
add first version of model averaging visualization
2017-09-26 19:25:37 +02:00
run_model.sh
move model creation back into models package
2017-11-07 20:09:20 +01:00
run.sh
add first version of model averaging visualization
2017-09-26 19:25:37 +02:00
server.py
remove identical parameter from data loading function; add runs argument
2017-11-07 20:47:41 +01:00
test.sh
add parser argument for naming in multi model modes, minor fixes, re-set fix vals for network - need to make them flexible
2017-09-05 17:40:57 +02:00
utils.py
add bulk embedding visualization and deep1 network
2017-10-09 14:19:01 +02:00
visualize.py
add TSNE embedding; server evaluation visualization
2017-10-19 17:39:37 +02:00

README.md

This is the init commit for my master thesis project.

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Description
My master thesis project on malware detection using neural networks and multi task learning
Readme
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Python 99.7%
Makefile 0.3%