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Project Setup

This document provides instructions on setting up the project environment for both the local experimental part and the deployment part. It includes separate sections for each aspect.

Local Experimental Setup

Prerequisites

  • Python (version 3.6 or above)
  • pip (package installer for Python)
  • Jupyter Notebook

Setup Steps

  1. Clone the repository:

    git clone https://github.com/your-username/your-project.git
cd your-project

  2. Create a virtual environment (optional but recommended):

    python3 -m venv venv
source venv/bin/activate

  3. Install the required dependencies:

     pip install -r requirements.txt

  4. Start Jupyter Notebook:

    jupyter notebook

  5. Open the desired notebook from the notebooks directory and run it.

Note for Deep Learning Models: The notebooks related to deep learning models, such as the DNN implemented in TensorFlow, require TensorFlow to be installed. Please refer to the official TensorFlow installation guide at https://www.tensorflow.org/install to choose your preferred installation method and install the appropriate version of TensorFlow based on your system and requirements.

For more specific information on using the balanced models and their training process, please refer to the README.md file in the notebooks/balanced directory.

Deployment Setup

Prerequisites

  • Docker
  • Kubernetes (Minikube is recommended for local deployment)

Setup Steps

  1. Follow the instructions in the README.md file to build the Docker image and deploy the model container.

  2. Follow the instructions in the README.md file to deploy the model container using Kubernetes.