Dataset Card for CuratedMNIST This dataset is a curated version of the classic MNIST dataset, enriched with model predictions, embeddings, and various analytical fields generated using the FiftyOne library. It was created as part of the "Image Classification and Dataset Curation with FiftyOne and PyTorch" tutorial to demonstrate practical computer vision workflows. The dataset contains the original 60,000 training and 10,000 test samples, with the training set further split into training (85%) and validation (15%) subsets. It includes predictions from OpenAI's CLIP model (zero shot), a custom trained LeNet 5 model, and a final LeNet 5 model that was fine tuned on an augmented set of challenging samples. This structure makes it ideal for educational purposes, allowing users to explore model comparison, error analysis, and data centric AI techniques. This is a FiftyOne dataset with 70000 samples. Installation If you haven't already, install FiftyOne: Usage Dataset Description This curated version of MNIST serves as a comprehensive resource for learning and experimenting with image classification workflows. Starting with the original MNIST dataset, this version adds multiple layers of…
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