This repository is meant for the analysis of time series forecasting state of the art for cryptocurrency applications.
It is made in the context of the course IFT-6759: Advanced ML project
├── LICENSE
├── Makefile <- Makefile with 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.
│
├── 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`.
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
└── src <- Source code for use in this project.
├── __init__.py <- Makes src a Python module
│
├── data <- Interface for local datasets
│ └── ...
│
├── gdrive <- Scripts to download or generate data
│ └── ...
│
└── pipeline <- Scripts to train models and then use trained models to make
│ predictions as well as hyper parameter search
└── ...
This project uses makefiles to automate the common workflows within the pipeline
To get started with this project install make, then type make in your terminal. This will list available commands
Then type make create_environment, make requirements and finally make test_environment to verify the setup.
Project based on the cookiecutter data science project template. #cookiecutterdatascience