Iris Classification Project

Features

• Data processing script for the Iris dataset.
• Dockerized environment for training and inference.
• PyTorch model for classification.

Prerequisites

• Docker
• Python
• Python libraries

Project Structure

• training/: Training scripts and Dockerfile.
• inference/: Inference scripts and Dockerfile.
• shared_folder/: Contains PyTorch model and model predictions.
• .gitignore: Specifies untracked files.
• README.md: Project description and instructions.

Setup and Running

• Download the ZIP file of repo
• Create a folder named shared_folder in main folder

  Training

  First, navigate to the 'training' directory. Build the Docker image for training:

• docker build -t iris_training_image .

Run the training container:

• docker run -v /path/to/shared_folder:/app/shared_folder iris_training_image

Inference

First, navigate to the 'inference' directory. Build the Docker image for inference:

• docker build -t iris_inference_image .

Run the inference container:

• docker run -v /path/to/shared_folder:/app/shared_folder iris_inference_image