MLOps course at MISIS 2024
Project description
Репозиторий курса MLOps
Аллаяров Тимур, БИВТ-21-17
Project Organization
├── LICENSE <- Open-source license if one is chosen
├── Makefile <- Makefile with convenience commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── docs <- A default mkdocs project; see www.mkdocs.org for details
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
│
├── pyproject.toml <- Project configuration file with package metadata for
│ src and configuration for tools like black
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.cfg <- Configuration file for flake8
│
└── src <- Source code for use in this project.
│
├── __init__.py <- Makes src a Python module
│
├── config.py <- Store useful variables and configuration
│
├── dataset.py <- Scripts to download or generate data
│
├── features.py <- Code to create features for modeling
|
├── preprocessing.py <- Code to create preprocess data after dataset.py
│
├── modeling
│ ├── __init__.py
│ └── train.py <- Code to train models
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├── entities
│ ├── __init__.py
│ └── params.py <- Code to read configuration params from params.yaml
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│
└── report.py <- Code to write metrics, create visualizations and report
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