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Datasets

by @stats385 · 5 nodes · curated

Canonical vision benchmarks used throughout the course: MNIST, CIFAR-10, ImageNet.

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Karpathy — Competing Against a ConvNet on ImageNet karpathy.github.io · Sep 24 karpathy.github.io · Sep 24
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Human-vs-convnet notes — useful perspective piece for students.

ImageNet (overview) en.wikipedia.org · Sep 24 en.wikipedia.org · Sep 24
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Background on ILSVRC and why ImageNet mattered historically for deep learning.

ImageNet image-net.org · Sep 24 image-net.org · Sep 24
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Large-scale image database that powered AlexNet and the modern deep learning boom.

CIFAR-10 cs.toronto.edu · Sep 24 cs.toronto.edu · Sep 24
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60k 32×32 color images, 10 classes. Standard small-scale vision benchmark for theory papers.

MNIST yann.lecun.com · Sep 24 yann.lecun.com · Sep 24
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60k train / 10k test handwritten digits, 28×28. The ‘hello world’ of classification.