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Poultry Disease Identification

Poultry diseases pose a significant threat to both the health of birds and the overall production efficiency of poultry farms. Early identification of these diseases through fecal analysis is essential for implementing timely interventions. This process not only helps in maintaining flock welfare but also enhances productivity, ensuring a healthier farm ecosystem.

17 lectures

What You Will Learn

Master the end-to-end Machine Learning lifecycle from data ingestion to deployment.
Learn to write modular, production-grade Python code for Deep Learning projects using CNNs.
Understand MLOps principles including automated pipelines with DVC.
Gain hands-on experience with Containerization using Docker.
Implement CI/CD pipelines using GitHub Actions for automated deployment.
Build and deploy scalable APIs using Flask.
Deploy applications to Cloud platforms Azure.

System Architecture

Poultry Disease Identification Architecture Diagram

High-level architecture overview of the Poultry Disease Identification .

What You'll Build

  • A "Poultry Disease Identification" application using VGG16 (Transfer Learning).
  • An automated Training Pipeline that handles data ingestion, base model preparation, training, and evaluation.
  • A Prediction Pipeline exposed via a Flask web application for real-time image classification.
  • An automated deployment workflow using Docker and GitHub Actions.
Poultry Disease Identification
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