AI/ML Image Classification using CNN (CIFAR-10 Dataset)

This project demonstrates the implementation of a Convolutional Neural Network (CNN) to perform supervised image classification on the CIFAR-10 dataset. The goal was to build, train, evaluate, and visualize the performance of a model that classifies images into one of ten predefined categories.

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📌 Project Overview

• Dataset: CIFAR-10
• Model Type: Convolutional Neural Network (CNN)
• Framework: TensorFlow / Keras
• Languages Used: Python
• Evaluation Metrics: Accuracy, Loss
• Visualization: Matplotlib (for predicted vs actual labels)

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🚀 Features

• Preprocessing of image data
• CNN architecture built with Keras
• Model training and validation with real-time accuracy/loss monitoring
• Final model evaluation using batch-based testing
• Visualization of 10 randomly selected predictions vs. actual labels
• Error analysis for misclassified images

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🧠 Classes in CIFAR-10