LSTM

所属分类:网络编程
开发工具:Python
文件大小:95KB
下载次数:17
上传日期:2018-12-18 12:40:05
上 传 者妙涵蝶
说明:  采用深度学习LSTM算法分析时间序列问题
(Time Series Analysis Using Machine Learning Algorithms)

文件列表:
config.json (765, 2018-10-16)
core (0, 2018-10-16)
core\__init__.py (362, 2018-10-16)
core\data_processor.py (3562, 2018-10-16)
core\model.py (4274, 2018-10-16)
core\utils.py (237, 2018-10-16)
data (0, 2018-10-16)
data\sinewave.csv (61721, 2018-10-16)
data\sp500.csv (310533, 2018-10-16)
requirements.txt (82, 2018-10-16)
run.py (2870, 2018-10-16)

# LSTM Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wave and stock market data. [Full article write-up for this code](https://www.altumintelligence.com/articles/a/Time-Series-Prediction-Using-LSTM-Deep-Neural-Networks) [Video on the workings and usage of LSTMs and run-through of this code](https://www.youtube.com/watch?v=2np77NOdnwk) ## Requirements Install requirements.txt file to make sure correct versions of libraries are being used. * Python 3.5.x * TensorFlow 1.10.0 * Numpy 1.15.0 * Keras 2.2.2 * Matplotlib 2.2.2 Output for sine wave sequential prediction: ![Output for sin wave sequential prediction](https://www.altumintelligence.com/assets/time-series-prediction-using-lstm-deep-neural-networks/sinwave_full_seq.png) Output for stock market multi-dimensional multi-sequential predictions: ![Output for stock market multiple sequential predictions](https://www.altumintelligence.com/assets/time-series-prediction-using-lstm-deep-neural-networks/sp500_multi_2d.png)

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