Project for Inżynieria Uczenia Maszynowego class.

The scope of this project is to propose a classifier based on Smart Grid Stability dataset: https://www.kaggle.com/pcbreviglieri/smart-grid-stability while using proper ML tools in a correct way.

Zadanie 1

script.sh downloads and unzips the dataset and executes python_script.sh, which then normalizes the data, divides the dataset into train, test and validation subsets and prints a short summary of the dataset as well as its subsets.

Zadanie 2

add Jenkinsfiles and mock data preprocessing

Zadanie 4

added lab4 directory with new python script and updated Dockerfile. The container downloads the dataset and installs software needed, then trains and evaluates model on the dataset. Loss and accuracy are saved to test_eval.txt file.

Zadanie 5

added lab5 directory with scripts

Zadanie 6

added create, train, eval directories in lab5

Zadanie 7

updated contents of lab5/train directory

Zadanie 8

didn't manage to do the task

Zadanie 9

added lab9 directory with .yaml file containing the description of the python environment used for the development of previous tasks

Zadanie 10

added data directory as well as dvc related files for subtasks 1-4, did not attempt subtask 5

ium01.ipynb is a notebook used to develop previously mentioned scripts.