This repo built neural networks completely from scratch using just NumPy and trained them on the MNIST dataset from Samson Zhang. The goal was to deeply understand how neural networks work under the hood — from forward and backward propagation to gradient descent and weight updates. No TensorFlow or PyTorch here, just pure math and code!
active 2025-03-29 → 2025-03-29 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2025-03-29 to 2025-03-29. Pushes: 2 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
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- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| dev-tr26 | 2 | 2 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.