Machine Learning Dashboard React App

Welcome to the Machine Learning Dashboard React App! This application is designed to provide comprehensive analytics for products, including revenue and expense trends. It also includes a machine learning model to predict next year's revenue based on historical data.

Table of Contents

• Features
• Getting Started
• Usage
• Technologies Used
• Installation
• Configuration
• Contributing

Features

• View detailed analytics of products, revenue, and expenses.
• Interactive charts and graphs for visual representation of data.
• Machine learning prediction for next year's revenue based on historical data.

Getting Started

Follow these steps to get the project up and running on your local machine:

1. Clone this repository: git clone https://github.com/your-username/ml-dashboard-react-app.git
2. Navigate to the project directory: cd ml-dashboard-react-app
3. Install the required dependencies: npm install
4. Start the development server: npm start
5. Open your web browser and go to: http://localhost:3000

Usage

Once the app is running, you can explore the different analytics and visualizations available for products. You can also use the machine learning prediction feature to estimate next year's revenue based on historical revenue and expense data.

Technologies Used

• React: A JavaScript library for building user interfaces.
• Redux: A state management library for managing application state.
• Chart.js: A charting library to create interactive charts and graphs.
• Machine Learning Model (Python): A machine learning model trained to predict future revenue based on historical data.

Installation

Make sure you have Node.js and npm (Node Package Manager) installed on your machine.

1. Clone the repository: git clone https://github.com/your-username/ml-dashboard-react-app.git
2. Navigate to the project directory: cd ml-dashboard-react-app
3. Install dependencies: npm install
4. Start the app: npm start

Configuration

You might need to configure the backend API endpoints and database connections for fetching and storing data. Update the relevant configuration files in the project.

Contributing

Contributions are welcome! If you'd like to contribute to this project, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix: git checkout -b feature-name
3. Commit your changes: git commit -m "Description of your changes"
4. Push to the branch: git push origin feature-name
5. Open a pull request and describe your changes.