Mlops-ml-deploy-made-iv 0.8

Mlops-ml-deploy-made-iv

# mlops_made_2022

### Настройка окружение:

1. `python3 -m venv .venv`

2. `source .venv/bin/activate`

3. `pip3 install -r requirements.txt`

### Make directory for logs and results (if there aren’t these folders in actual commit): `mkdir src/logs && mkdir results` ### ML pipeline start with commands: #### Training: `python3 -m src.model_pipeline --process-type=train configs/<config's name>` #### Evaluating: `python3 -m src.model_pipeline --process-type=predict configs/<config's name>` ### Configs: 1) `logistic_regression_config.yaml` - model with logistic regression 2) `random_forest_config.yaml` - model with random forest #### Preprocessing pipeline can be corrected with changing `preprocessing_params`. There are three different type of preprocessing in configs: `normalization`, `polynomial`, `k-bin` ### Tests: Tests start with `python3 -m unittest discover -s ./tests -p 'test_*.py'` ### Output data: 1) `results/metrics.json` - result of predict-process 2) `src/logs/logs.log` - logs of all scripts

### Other: requirements.txt was created with console command: `pip3 freeze | grep -v hw01 > requirements.txt` - all libs were saved like this .gitignore and global .gitignore was created with console command: 1) `curl -o .gitignore https://raw.githubusercontent.com/github/gitignore/master/Python.gitignore` - and add -idea 2) `curl -o $HOME/.gitignore_global https://raw.githubusercontent.com/github/gitignore/master/Global/Linux.gitignore`