Predict Stock Prices Using RNN: Part 2
A tutorial on using Recurrent Neural Networks (RNNs) to predict stock prices continues from Part 1. The author adds the ability for the RNN to respond to multiple stocks by incorporating stock symbol embedding vectors into the input. This technique is used to identify patterns in different price sequences.
A tutorial on using Recurrent Neural Networks (RNNs) to predict stock prices continues from Part 1. The author adds the ability for the RNN to respond to multiple stocks by incorporating stock symbol embedding vectors into the input. This technique is used to identify patterns in different price sequences.
---
Why it matters: This matters because it shows how to use RNNs to analyze and make predictions on complex time-series data, such as stock prices. This can be useful for researchers and engineers working with financial or sensor data.
Source: https://lilianweng.github.io/posts/2017-07-22-stock-rnn-part-2/
This article was originally published at: https://lilianweng.github.io/posts/2017-07-22-stock-rnn-part-2/