Home / Factor research
Deep Learning Machine Learning Stock
Jupyter notebooks applying deep learning to stock prediction
What it is
A collection of Jupyter notebooks that study and analyze stocks using deep learning and machine learning techniques. The notebooks apply a range of ML and DL algorithms to predict stock behavior, using both technical and fundamental analysis for long-term and short-term predictions, and explore why certain methods work or fall short. Traders and investors who want a comprehensive, hands-on study of AI-based stock strategies will find it useful. This is research and educational material rather than a finished trading product, so experimentation and adaptation are left to the user.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Beginners |
|---|---|
| Used for | Strategy research, Data analysis |
| Markets | US equities |
| Stack | Python |
| Learning curve | Easy to start |
| Practical value | Medium 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): −1 over the period, now 1,788. Gaps mean no snapshot was taken that day.
Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.