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Solar Panel Defect Classification Using Deep Learning

This project focuses on building and deploying image classification models using various architectures. Students will gain hands-on experience with model training, hyperparameter optimization, and deployment on AWS EC2, culminating in a functional image classification service.

18 lectures

What You Will Learn

Understanding fundamental concepts in image classification.
Building baseline image classification models.
Mastering model training and evaluation techniques.
Implementing transfer learning with pre-trained models (MobileNetV2, EfficientNet).
Applying hyperparameter optimization techniques to improve model performance.
Building interactive applications using Streamlit.
Deploying machine learning models on AWS EC2.

System Architecture

Solar Panel Defect Classification Using Deep Learning Architecture Diagram

High-level architecture overview of the Solar Panel Defect Classification Using Deep Learning .

What You'll Build

  • A baseline image classification model.
  • Image classification models using MobileNetV2 and EfficientNet.
  • A Streamlit application for image classification.
  • A deployed image classification service on AWS EC2.
Solar Panel Defect Classification Using Deep Learning
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