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This code is the work of a semester's long course and is here presented with the intent to highlight the acquired skills in ML and DL.

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Sistemas Inteligentes para Bioinformática

Curricular Unit

"Intelligent Systems for Bioinformatics" integrated in the Bioinformatics Master Degree at University of Minho, 2022-2023

Description

A package of machine learning algorithms to grasp the concepts of the course. Students should implement essential algorithms from scratch using numpy and pandas. Implementations must follow a common and simple API.

Setup

To get started, fork the repository from GitHub and clone it to your local machine.

Fork the following GitHub repository: https://github.com/cruz-f/si img.png

Then, clone the repository to your local machine:

git clone https://github.com/YOUR_USERNAME/si.git

Open the repository in your favorite IDE and install the dependencies (if missing):

pip install -r requirements.txt

or

pip install numpy pandas scipy matplotlib

Note: You can also create a similar Python package and push it to your GitHub.

Make a change to the repository: Add your co-authorship to the __init__.py file (within the si folder):

__author__ = "YOUR_NAME" 
__credits__ = ["YOUR_NAME"]
__license__ = "Apache License 2.0"
__version__ = "0.0.1"
__maintainer__ = "YOUR_NAME"
__email__ = "YOUR_EMAIL"

Then, commit it to your local repository and publish it to your GitHub:

git add README.md
git commit -m "Adding my co-authorship to README.md file"
git push origin main

Note: you can also use the IDE Git tools.

Architecture

The package is organized as follows:

si
├── src
│   ├── si
│   │   ├── __init__.py
│   │   ├── data
│   │   │   ├── __init__.py
├── datasets
│   ├── README.md
│   ├── ...
├── scripts
│   ├── README.md
│   ├── ...
├── ... (python package configuration files)

A tour to Python packages:

  • The src folder contains the source code of the package. It should contain an intermediate file called si (the name of the package) and the modules of the package. All python packages and subpackages must also contain a file called __init__.py.
  • The datasets folder contains the datasets used in the scripts.
  • The scripts folder contains the scripts used to test the package and include examples.

Note: It is also common to have a tests folder to include the unit tests of the package. However, we will not cover this topic in this course.

Note: A python package also contains many configuration files (e.g., setup.py, requirements.txt, etc.).

Credits

This package is heavily inspired and adapted by Vítor Pereira.

About

This code is the work of a semester's long course and is here presented with the intent to highlight the acquired skills in ML and DL.

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  • Jupyter Notebook 97.5%
  • Python 2.5%