Predicting stock prices for tech giants like Amazon, Apple, and Google using Recurrent Neural Networks (RNN) and Long Short-Term Memory networks (LSTM). Delve into time-series analysis, model training, and forecast accuracy with Jupyter Notebooks. Uncover insights into leveraging advanced neural networks for stock market predictions.
active 2024-01-18 → 2024-05-22 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 126 days from 2024-01-18 to 2024-05-22. Pushes: 0 total, peak 0 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
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
Nobody pushed, opened or commented here in the loaded window — this repo's activity is stars and forks only.
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.