Stock price prediction
Sequential models such as RNNs are naturally well suited to time series prediction—and one of the most advertised applications is the prediction of financial quantities, especially prices of different financial instruments. In this recipe, we demonstrate how to apply LSTM to the problem of time series prediction. We will focus on the price of Bitcoin—the most popular cryptocurrency.
A disclaimer is in order: this is a demonstration example on a popular dataset. It is not intended as investment advice of any kind; building a reliable time series prediction model applicable in finance is a challenging endeavor, outside the scope of this book.
How to do it...
We begin by importing the necessary packages:
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM
from sklearn.preprocessing import MinMaxScaler
The...