Show HN: 78% MNIST accuracy using GZIP in under 10 lines of code

• umap_paper_notebooks

  1 41 10.0 Jupyter Notebook

  Notebooks in support of the UMAP paper

In fairness you can run MNIST through UMAP and get near perfect seperation. I'm of the belief that you have to try pretty hard not to do well on MNIST these days.

https://github.com/lmcinnes/umap_paper_notebooks/blob/master...

• hlb-CIFAR10

  36 1,187 3.5 Python

  Train CIFAR-10 in <7 seconds on an A100, the current world record.

If you'd like to play around with MNIST yourself, I wrote a PyTorch training implementation that gets ~95.45%+ in <13.6 seconds on a V100, est. < 6.5 seconds on an A100. Made to be edited/run in Colab: https://github.com/tysam-code/hlb-CIFAR10

It's originally kitted for CIFAR10, but I've found the parameters to be quite general. The code is very easy to read and well-commented, and is a great starting place for exploration.

Min-cut deltas to run MNIST:

`.datasets.CIFAR10('` -> `.datasets.MNIST('` (both occurences)

• InfluxDB

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• mono

  1 5 6.7 Python

  monorepo for personal projects, experiments, .. (by Jakob-98)

• mnist_1_pt_2

  1 16 5.3 Python

  1.2% test error on MNIST using only least squares and numpy calls.

ben recht's kernel method implementation in 10 lines hits 98%

https://github.com/benjamin-recht/mnist_1_pt_2/tree/main

• label-errors

  7 176 0.0

  🛠️ Corrected Test Sets for ImageNet, MNIST, CIFAR, Caltech-256, QuickDraw, IMDB, Amazon Reviews, 20News, and AudioSet

  

Sadly,there are several errors in the labeled data, so no one should get 100%.

See https://labelerrors.com/

• WorkOS

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