Week 2 - AICTE Edunet Internship (Image Classification)

📘 Objective

Build a Convolutional Neural Network (CNN) to classify waste images into categories using the Waste Classification Dataset from Kaggle.

🧠 Steps Done

1. Loaded dataset from Kaggle
2. Used ImageDataGenerator for preprocessing
3. Built CNN model with TensorFlow/Keras
4. Trained model for 4 epochs
5. Visualized accuracy and loss graphs
6. Evaluated model performance

📊 Results

Achieved test accuracy around 85–90% (varies slightly each run).

🔗 Dataset

Kaggle - Waste Classification Dataset