Abschluss Arbeit (Bachelor Thesis)

Code Descriptions

data_processing.py: Plots the information received from pid_data_acq.py.
network_acq.py: Acquire the network benchmark metrics such as bandwidth, jitter and others. DISCLAIMER: It is not working propperly.
pid_data_acq.py: Acquire the necessary monitoring data such as CPU usage, network traffic and memory usage.

training_data.py: Plots the results acquired trough the training json exported file.
pc_data.py: Updated version of data_processing.py. Plots the hardware usage troughout the training.

metrics_matrix.py [Outdated]: Plots the confusion matrix and gives the overall value of the main metrics (Accuracy, Loss and F1).
/Sandbox/ functions_matrix.py: Library containing functions to open model, data, evaluate and plot the confusion matrix.
/Sandbox/ main_matrices.py: Main script running the created fm library.

Obs:

0311: npz0, npz3(tmnist2), npz4
0007: npz1, npz2, npz3(tmnist1)

Last updated on 18/04/2024

Name		Name	Last commit message	Last commit date
Latest commit History 21 Commits
Official Xp		Official Xp
cnn visual		cnn visual
figs		figs
hardware metrics		hardware metrics
metrics		metrics
monolythic test		monolythic test
outdated files		outdated files
testing models		testing models
timestamp		timestamp
0007_FedAvg_xp2.png		0007_FedAvg_xp2.png
0311_fedSDG_xp5.png		0311_fedSDG_xp5.png
README.md		README.md
my_keras_model2.png		my_keras_model2.png
trained_model.h5		trained_model.h5
v1.5_TCC_Hans.pdf		v1.5_TCC_Hans.pdf