CIFAR10 classification using Machine Learning and Deep Learning Models
CIFAR10 classification using Machine Learning and Deep Learning Models by Team 21 Vyshnavi Chalechimala, Apurva Mandalika, Priyanka Verma, Vaishnavi Chakradeo, Jawahar Sai Nathani Image recognition is at the heart of modern machine learning, fueling innovations in fields like self-driving cars, healthcare, and augmented reality. In this blog post, we’ll dive into the world of image classification using the CIFAR-10 dataset—a benchmark dataset of 60,000 tiny images spread across 10 distinct categories. What Is CIFAR-10? The CIFAR-10 dataset is among the most well-known benchmarks for image classification tasks, offering researchers and practitioners a comprehensive playground for experimenting with various machine learning and deep learning algorithms. This dataset is a labeled subset of the 80 Million Tiny Images dataset, collected by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. Overview Total Images : 60,000 Image Size : 32x32 pixels (color images) Number of C...