This repository contains neural network written from scratch only using numpy library. I have used gradient descent to optimise the weights and bias. Sum of Squared error is used to calculate loss. It is a single node perceptron that uses sigmoid as activation function. Since sigmoid is used this works well only for data that has two classes.
active 2024-09-01 → 2024-09-01 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-09-01 to 2024-09-01. Pushes: 1 total, peak 1 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.
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Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| danush02 | 1 | 1 | 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.