Sci-template

This template made by Zherish Galvin Mayordo is tailored for data enthusiasts. The modules for this template were originally used for a specific deep learning study that were redesigned to be flexible and modular.

How to use this template

1. Make sure to install Anaconda or Miniconda before using this template. You can install either of them at this link.
2. Create a new environment for this template using the command conda env create -f environment.yml -n [ENVIRONMENT_NAME], for CUDA-enabled systems, OR conda env create -f environment-noncuda.yml -n [ENVIRONMENT_NAME], for non-CUDA-enabled systems.
3. Activate the new environment: conda activate [ENVIRONMENT_NAME].
4. Verify that the new environment was installed correctly: conda list
5. Once verified, run setup.cfg using pip install .

Note: This package already includes tensorflow and scikit-learn.
Note: This package is created using Windows 10 operating system.
Note: You can also verify if tensorflow is installed properly using the command: python -c "import tensorflow as tf; print(tf.config.list_physical_devices())"

Author details

If you want to reach out to me, here's my contact details:

Name: Zherish Galvin Mayordo
Email: zherishatbusiness@gmail.com
LinkedIn: https://www.linkedin.com/in/zgmayordo

If you want to contribute, here are the committing guidelines:

1. [fix]: For bug fixes.
2. [update]: For updating code's functionality.
3. [feat]: For adding new feature/s.
4. [style]: For changes that do not affect the code's functionality (e.g., formatting, spacing).
5. [docs]: For documentation changes.
6. [refactor]: For code refactoring without changing its external behavior.
7. [perf]: For performance improvements.
8. [chore]: For maintenance tasks, tooling changes, or other non-code changes.
9. [dependency]: For updates or changes related to dependencies.
10. [security]: For security-related changes.
11. [cleanup]: For removing redundant code or files.
12. [merge]: For merge commits.