shub-garg/Vision-Transformer-VIT-for-MNIST
This repository implements a Vision Transformer (ViT) to classify handwritten digits from the MNIST dataset. The project includes model definition, training scripts, and visualization of results, including correct/incorrect predictions and a confusion matrix.
This project helps machine learning practitioners classify handwritten digits. You feed it a dataset of handwritten digit images, and it outputs a trained model that can identify digits, along with visualizations of its performance, including correct and incorrect predictions and a confusion matrix. Anyone working on building or evaluating image classification models for digit recognition would use this.
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Use this if you are a machine learning engineer or data scientist specifically interested in understanding or applying Vision Transformers for image classification tasks, particularly on well-known datasets like MNIST.
Not ideal if you need a pre-trained, production-ready model for digit recognition or if your task involves complex, real-world image classification beyond simple digits.
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May 29, 2024
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