Stock Market Prediction

• Tech Stack: Python, Sklearn, Tensorflow, Pandas, Matplotlib, Numpy
• Github URL: Project Link

The project uses deep learning techniques, specifically LSTM networks implemented with TensorFlow, to predict stock market trends.

TensorFlow, an open-source deep learning framework, is utilized as the platform for implementing the LSTM-based model. LSTM networks are a type of recurrent neural network that excel at capturing long-term dependencies in sequential data.

The project aims to leverage deep learning and LSTM networks to make accurate forecasts about future stock market behavior. By training the model on historical market data, it seeks to identify patterns and relationships that can be used to predict future price movements, providing valuable insights for investors.