The code loads a pre-trained LSTM model to predict Bitcoin prices. It fetches historical Bitcoin price data using the yFinance library. The data is normalized and split into training and testing sets. The LSTM model is used to predict future prices based on the test data. Predictions and actual prices are visualized in Streamlit.
active 2024-09-13 → 2025-03-08 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 177 days from 2024-09-13 to 2025-03-08. Pushes: 4 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: 4 total, peak 1 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- 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 |
|---|---|---|---|---|
| pythonophile | 4 | 4 | 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 — 4 stars here means stars gained during the window, not the repo's star count.