A ML for finance market news prediction
- Make >= 4.3
├── LICENSE
├── Makefile <- Makefile with commands like 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.
│
├── models <- Trained and serialized models
│
├── notebooks <- Jupyter notebooks.
│
├── 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.
The data folder is not present on the repository and must be made on each person clone, in most cases the notebooks we'll cite some csv that are not present in this repo, if the data is required please send an email to lkazu@duck.com
We reccommend the utilization of vscode for developing using docker
Use the following make command:
make dockerand connect to the container using dev containers.
All changes will persist since we are using volumes.
Dependencies required:
- Conda >= 23.3.1
Use the following make command:
make initall dependencies will be installed, and you should be in the conda enviroment.
Project based on the cookiecutter data science project template. #cookiecutterdatascience