Stock Price Prediction with LSTM
<p>How to Predict Stock Prices with LSTMs</p>
<p>LSTMs are a type of recurrent neural network that are well-suited for time series prediction tasks. In this blog post, we will use an LSTM to predict the stock price of Apple Inc. (AAPL) using historical data.</p>
<p>The first step is to load the data. We will use the <code>pandas</code> library to load the data from a CSV file. The data contains the daily closing price of AAPL from January 1, 2010, to December 31, 2022.</p>
<p>Once the data is loaded, we need to split it into training and test sets. The training set will be used to train the LSTM model, and the test set will be used to evaluate the model’s performance.</p>
<p><a href="https://medium.com/@sakshisanghi0001/stock-price-prediction-with-lstm-3784c246530b"><strong>Read More</strong></a></p>