Predicting Stock Prices Using LSTM: An Analysis of Time Series Data
This project explains how to develop an end-to-end data science model using Alpha Vantage APIs and Long Short-Term Memory (LSTM) machine learning algorithms for predicting stock price movements.
As a result of completing this project, you will learn the key concepts of machine learning / deep learning and build a fully functional stock market prediction model in Python.
Due to the inherent complexity and uncertainty of financial markets, predicting stock prices has always been challenging. Advances in deep learning techniques, such as Long Short-Term Memory (LSTM) neural networks, have shown promise in capturing temporal patterns and making accurate predictions. Using historical data, we apply LSTM models to predict stock prices. To understand the performance of the model, we use a comprehensive approach that includes data preprocessing, model training, and evaluation.
Download the source code by clicking the link in comment box.