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bulbea
Deep learning library for stock prediction and backtesting
What it is
A Python library for stock market prediction and modelling built on deep learning. It loads share data, splits it into training and testing sets, trains models via Keras and TensorFlow, and includes sentiment analysis using Twitter credentials with Tweepy and TextBlob. Quant developers and researchers experimenting with neural network approaches to market prediction may find it a useful starting point. The project is research-oriented code rather than a finished product, and it depends on external services such as Quandl and Twitter API access.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Developers |
|---|---|
| Used for | Backtesting, Strategy research |
| Markets | US equities |
| Stack | Python |
| Learning curve | Moderate learning curve |
| Practical value | Low practical value |
| Cost | Free and open source |
| Hardware | GPU optional |
| Maintenance | No commits in over six months |
GitHub stars, last 30 days
Daily snapshots since 2026-09-12 (up to 30 days): +10 over the period, now 2,338. Gaps mean no snapshot was taken that day.
Deep Learning based Python Library for Stock Market Prediction and Modelling.
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