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Beginner shares neural network weights for MNIST classification

By PulseAugur Editorial · [1 sources] ·

A user has shared the weights for a neural network they developed to classify MNIST handwritten digits. The network features two hidden layers with 64 and 32 neurons respectively, and an output layer with 10 neurons. This project, representing the user's first foray into machine learning, achieved an accuracy of 96.52% on the MNIST dataset. AI

IMPACT Demonstrates a foundational project for learning neural network implementation and evaluation.

RANK_REASON This is a personal project release of model weights for a well-known dataset, not from a major lab or institution. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/MachineLearning →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Beginner shares neural network weights for MNIST classification

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2 / 100
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Tool
This is a personal project release of model weights for a well-known dataset, not from a major lab or institution. [lever_c_demoted from research: ic=1 ai=1.0]
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Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release
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High
Clearly on-topic for AI-industry coverage.
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Same-day
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COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/Rollgus ·

    Weights for MNIST Handwriting Network [P]

    <table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1xupgn8/weights_for_mnist_handwriting_network_p/"> <img alt="Weights for MNIST Handwriting Network [P]" src="https://preview.redd.it/sfl0qf5b291i1.png?width=140&amp;height=94&amp;auto=webp&amp;s=5d303a539…

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