愉快的学习就从翻译开始吧_Multivariate Time Series Forecasting with LSTMs in Keras_8_Further Reading&Summary

Further Reading/进一步阅读

This section provides more resources on the topic if you are looking go deeper.

如果您想更深入研究，本节将提供更多有关该主题的资源。

• Beijing PM2.5 Data Set on the UCI Machine Learning Repository
• The 5 Step Life-Cycle for Long Short-Term Memory Models in Keras
• Time Series Forecasting with the Long Short-Term Memory Network in Python
• Multi-step Time Series Forecasting with Long Short-Term Memory Networks in Python

Summary/总结

In this tutorial, you discovered how to fit an LSTM to a multivariate time series forecasting problem.

在本教程中，您了解了如何将LSTM应用于多变量时间序列预测问题。

Specifically, you learned:

具体来说，你了解到：

• How to transform a raw dataset into something we can use for time series forecasting.
  如何将原始数据集转换为我们可用于时间序列预测的东西。
  
• How to prepare data and fit an LSTM for a multivariate time series forecasting problem.
  如何准备数据并拟合多变量时间序列预测问题的LSTM。
  
• How to make a forecast and rescale the result back into the original units.
  如何进行预测并将结果重新调整回原始单位。
  

Do you have any questions?

Ask your questions in the comments below and I will do my best to answer.

你有任何问题吗？
在下面的评论中提出您的问题，我会尽我所能来回答。