JordiCorbilla / stock-prediction-deep-neural-learning
Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting
Why this job: matched by what the repo talks about: memory, term, long, learn
What it does
- TensorFlow LSTM models for price, return, delta and trend-residual targets.
- v7 direction + magnitude forecasting with recursive future inference.
- v8 shared multi-task LSTM architecture for direction and magnitude.
- Recorded experiment seeds and runtime metadata; exact numeric reproducibility can vary by hardware and backend.
- Training/validation/test separation for model fitting and evaluation.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 9 days ago
- Stars
- 689
- +1 this week
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v2.0
- Released 43 days ago
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 100% closed
- 0 still open
- Pull requests
- 9 merged
- 0 waiting
- Releases
- 7
- 3 in the last year
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
More: languages, topics and project record
Languages
- Python 100%
Topics
- machine-learning
- deep-learning
- deep-neural-networks
- yfinance
- lstm-neural-networks
- lstm-model
- recurrent-neural-networks
- stock-prediction
- stock-prices
- market-data
- finance
- cryptocurrency
Project record
- JobAgent memory
- StatusListed
- Commits369
- Forks128
- Watching17
- Stars in 28 days+2
- CreatedJul 1, 2020
- First seen by usNov 7, 2026
- CheckedNov 8, 2026