♻️ Waste Product Classifier — Transfer Learning & Fine-Tuning

Image classification model that automatically categorizes waste products using Transfer Learning and Fine-Tuning techniques.

🧠 About this project

Classifying waste correctly is a real-world problem with direct environmental impact. This project uses a pre-trained CNN model and applies Transfer Learning and Fine-Tuning to adapt it to waste product classification — achieving strong results without training from scratch.

🛠️ Tech Stack

• Python
• PyTorch
• Transfer Learning (pre-trained CNN)
• Fine-Tuning
• Jupyter Notebook

📊 Approach

1. Loaded a pre-trained convolutional neural network
2. Froze base layers to preserve learned features
3. Replaced the classification head for the waste categories
4. Fine-tuned the model on the waste dataset
5. Evaluated accuracy on validation data

📁 Files

• Final_Proj-Classify_Waste_Products_Using_TL-_FT-v1.ipynb — Main notebook

🎓 Context

Developed as part of the IBM AI Engineering Professional Certificate program.