Wise Trader

Predicting stock prices using machine learning models.

Table of Contents

• Introduction
• Features
• Data
• Getting Started
  • Prerequisites
  • Installation
• Usage
• Model Training
• Evaluation
• Contributing
• License
• Acknowledgements

Introduction

This project focuses on utilizing machine learning techniques to predict stock prices. It aims to provide insights into stock market trends and make predictions based on historical data.

Features

• Time Series Analysis: Utilize time series data analysis to understand historical stock price trends.
• Machine Learning Models: Implement machine learning models for stock price prediction.
• Visualization: Visualize stock price predictions and trends for better understanding.

Data

Explain where the data for your project comes from. This might include sources, data collection methods, and any preprocessing steps.

Getting Started

Provide instructions on how to get started with your project.

Prerequisites

List the prerequisites that users need to install or have available before they can use your project. For example:

• Python (version x.x.x)
• Jupyter Notebook
• Required Python libraries (NumPy, Pandas, Scikit-learn, etc.)

Installation

Provide step-by-step instructions for setting up the project environment and installing dependencies. Include code snippets where necessary.

# Clone the repository
git clone https://github.com/yourusername/stock-prediction.git

# Change to the project directory
cd stock-prediction

# Install required Python libraries
pip install -r requirements.txt