The Stocks Trend Predictor project aims to provide a tool for predicting the future trends of stock prices based on historical data. The prediction model utilizes machine learning algorithms to analyze patterns and make predictions about the direction of stock prices.
This repository contains a machine learning model for predicting the trend of stock prices using 100 data Mocing average and 200 days moving average. The project aims to analyze historical stock data and make predictions about future trends using various machine learning algorithms. By leveraging historical stock market data, this project can assist investors and traders in making informed decisions. This project includes the following key components:
- Python: The primary programming language for the project.
- Pandas: A library for data manipulation and analysis.
- Scikit-learn: A popular machine learning library for Python.
- Jupyter Notebook: An interactive development environment for running and sharing code.