lstm

Currency (FX) prediction using RNN [In the previous article, I tried to predict the stock price, so I will try to predict the forex market. As with stock prices, there are a variety of factors that can cause fluctuations, so it will be difficult to make a prediction using only a neural network model, but I’ll try it as an exercise in Keras. github The file in jupyter notebook format is here google colaboratory If you want to run it in google colaboratory here Author’s environment The author’s OS is macOS, and the options are different from Linux and Unix commands.
Stock prediction using RNN, LSTM RNN and LSTM are used for forecasting time series data. There are many kinds of time series data, such as temperature of a certain place, number of visitors, price of a product, etc. However, I would like to use RNN and LSTM to predict the stock price, which is the easiest data to obtain. However, neural nets can only make predictions within the scope of the data obtained, and the model is almost useless when the situation is unexpected.
Basics of keras and LSTM, Comparison with RNN LSTM stands for Long Short Term Memory, and is said to be able to learn long-term dependencies. LSTM is a type of RNN, and the basic idea is the same. I’m not going to go into the details, because you can find plenty of them by searching. Also, here is a comparison between LSTM and RNN. github The file in jupyter notebook format is here google colaboratory If you want to run it in google colaboratory here Author’s environment The author’s OS is macOS, and the options are different from Linux and Unix commands.