Author - Reethu yadav Welcome to the Stock Market Prediction project! This repository contains a machine learning model to predict stock prices and a user-friendly web application built with Streamlit to interact with the model.
Features Data Collection: Fetches historical stock price data from a reliable source. Data Preprocessing: Cleans and prepares the data for training the machine learning model. Model Training: Uses machine learning algorithms to predict future stock prices based on historical data. Interactive Web App: A Streamlit-based web application to visualize stock data and interact with the prediction model. Table of Contents Installation Usage Project Structure Model Description Web App Description Contributing Installation
Run the Streamlit app: streamlit run app.py Open your web browser and go to: Interact with the app to visualize stock data and predict future prices. Project Structure data/: Contains historical stock price data. notebooks/: Jupyter notebooks for exploratory data analysis and model development. models/: Trained machine learning models. app.py: Streamlit application README.md: Project documentation. Model Description The machine learning model used in this project is a [mention the algorithm, e.g., LSTM, ARIMA, etc.] model. It has been trained on historical stock price data to predict future prices. The model includes the following steps:
Data Preprocessing: Handling missing values, feature scaling, and splitting the data into training and test sets. Model Training: Training the model on the training set using [specific algorithm]. Evaluation: Evaluating the model’s performance using metrics such as MAE, RMSE, etc. Web App Description The Streamlit web application provides an interactive interface to:
Visualize Historical Data: Plot historical stock prices and trends. Predict Future Prices: Input a stock symbol and get the predicted future prices. Download Results: Download the predicted data for further analysis. Contributing We welcome contributions from the community! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.
License This project is licensed under the MIT License. See the LICENSE file for more details.
Happy Predicting! 🚀