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Data Mining and Machine Learning Algorithm Annotator

Overview

The ML Algorithms Annotator is a Django application which enables users to annotate and query ML algorithms. The algorithms information is based on an annotation schema and it includes entities like "Document", "Optimization Problem", "Complexity", etc. Additionally, the user can query the graph database containing multiple PoC algorithms like Linear Regreession, SVC, KNN, etc.

The development process is described in detail in Chapter 4 in my MSc thesis (p. 39).

Installation

Python dependencies

  1. Install with conda (using environment.yml) - TBD
    conda env create -f environment.yml
  2. Install with conda (using requirements.txt)
    conda create --name <env_name> --file requirements.txt
    conda activate <env_name>
  3. Install with venv
    python3 -m venv env_name
    source ee/bin/activate
    python3 -m pip install -r requirements.txt
  4. Install package - TBD
    pip install .

Node dependencies

  1. Install node.js
  2. cd into the frontend folder
    cd web-annotator/controller/frontend
  3. Install npm
    npm install -g npm
  4. Install dependencies
    npm i
  5. Compile the front-end
    npm run build - production
    npm run dev - development

Neo4j setup - TBD

Run the application

  1. cd to the controller folder
    cd web-annotator/controller
  2. Run the server
    python manage.py runserver

Support

lidija.jovanovska@outlook.com