"Image Processing and Classification Using Machine Learning - CIFAR-10 Project"

This project involves analyzing and processing image data from the CIFAR-10 dataset using libraries like NumPy, TensorFlow, and Scikit-Learn. The key steps implemented include:

Loading the dataset and separating images from their labels.

Reshaping the data to make it compatible with machine learning models.

Normalizing the values to enhance model performance.

Splitting the dataset into training and testing sets for better accuracy.

This project is ideal for anyone looking to develop an AI model for image classification using deep learning techniques and data preprocessing.