Welcome to Stock Trend Prediction Web Application in Python! This project leverages the power of machine learning, specifically Long Short-Term Memory (LSTM) models, to predict stock trends. The application is built using Streamlit, an open-source Python library that simplifies the process of creating interactive and visually appealing web applications for Machine Learning and Data Science.
Streamlit: Its integration is simple and efficient in creating web applications. With Streamlit, it is easy for users to interact with our stock trend prediction model through an intuitive and user-friendly interface.
LSTM Model: The underlying predictive power comes from an LSTM (Long Short-Term Memory) model. LSTMs are a type of recurrent neural network (RNN) that excels at capturing and learning patterns in sequential data, making them well-suited for time-series forecasting, such as predicting stock prices.