Stock Price Prediction Using Deep Learning: A Guide to Neural Networks, LSTM, and CNN

This article delves into the world of deep learning and its application in stock price prediction. We'll explore various neural network architectures, including:

• Neural Networks: The foundation of deep learning, neural networks are interconnected nodes that learn complex patterns from data. We'll discuss their role in stock price forecasting.
• Long Short-Term Memory (LSTM) Networks: LSTM networks are specifically designed to handle sequential data like time series. We'll explore how they excel at capturing long-term dependencies in stock prices.
• Convolutional Neural Networks (CNNs): CNNs are adept at identifying patterns within data. We'll investigate their use in extracting features from financial data for improved prediction accuracy.

By understanding these concepts, you can gain valuable insights into using deep learning to forecast stock prices and make more informed investment decisions.