This is a project for Advanced Machine Learning Course at innopolis university. It contains Seminars coding examples, homework exercises and Course project code.
- Keras >= 2.0.8
- TensorFlow >= 2.0
- Numpy >= 1.13.3
- Matplotlib >= 2.0.2
- Seaborn >= 0.7.1
- Catboost
- PyTorch
All the libraries can be pip installed using pip install -r requirements.txt
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Clone this repo (for help see this tutorial).
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Navigate to repository folder
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Install dependencies which are specified in requirements.txt. use
pip install -r requirements.txtorpip3 install -r requirements.txt -
Raw Data is being kept here within this repo.
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Data processing/transformation scripts are being kept here
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To run the repository main code nevigate to scr
cd srcthen runpython main.py. Or execute the .ipynb file here
cd AML-DS-2021
python -m venv dst-env
Max / Linux
source dst-env/bin/activate
Windows
dst-env\Scripts\activate
pip install -r requirements.txt
python setup.py
To run tests, install pytest and unittest using pip or conda and then from the repository root run
pytest tests
#or
python -m unittest discover -s tests/ -p '*_test.py' -v
├── .gitignore <- Files that should be ignored by git.
│
├── conda_env.yml <- Conda environment definition
├── LICENSE
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`. Might not be needed if using conda.
├── setup.py <- Setup script
│
├── data <- Data files directory
│ └── Data1 <- Dataset 1 directory
│
├── notebooks <- Notebooks for analysis and testing
│ ├── eda <- EDA Notebooks directory for
│ │ └── eda1.ipynb <- Example python notebook
│ ├── features <- Notebooks for generating and analysing features (1 per feature)
│ └── preprocessing <- Notebooks for Preprocessing
├── scripts <- Standalone scripts
│ └── dataExtract.py <- Data Extraction script
│
├── src <- Code for use in this project.
│ ├── train.py <- train script
│ └── test.py <- test script
│
└── tests <- Test cases (named after module)
├── test_notebook.py <- Test that Jupyter notebooks run without errors
├── test1package <- test1package tests
├── test1module <- examplemodule tests (1 file per method tested)
├── features <- features tests
├── io <- io tests
└── pipeline <- pipeline tests
Contributions to this repository are greatly appreciated and encouraged.
To contribute an update simply:
- Submit an issue describing your proposed change to the repo in question.
- The repo owner will respond to your issue promptly.
- Fork the desired repo, develop and test your code changes.
- Edit this document and the template README.md if needed to describe new files or other important information.
- Submit a pull request.
If you would like to get in touch, please contact: