This repository contains assignments and code from Andrew Ng's Neural Networks and Deep Learning course. It covers key concepts like forward/backpropagation, optimization, and neural network architectures, with detailed Jupyter Notebooks for hands-on practice. Perfect for tracking progress and revisiting core deep learning concepts!
active 2025-01-23 → 2025-03-01 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 38 days from 2025-01-23 to 2025-03-01. Pushes: 7 total, peak 4 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: 1 total, peak 1 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 |
|---|---|---|---|---|
| inder-dev-pro | 7 | 7 | 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 — 1 stars here means stars gained during the window, not the repo's star count.