Demo
Demo.-.DataPedictor.mp4
- Introduction
- Objective
- Features
- Architecture
- Requirements
- Application
- Usage Instructions
- Contributions
- License
- Authors
Data Predictor is a web application designed to facilitate the analysis of CSV data using AI models. Users can upload their datasets, select target columns, and receive predictions powered by advanced AI algorithms.
The main objective of this project is to provide an intuitive interface for users to upload their data and obtain predictions seamlessly. By leveraging PyCaret and FastAPI, this tool aims to simplify data analysis and empower users with actionable insights.
- Upload CSV files for analysis
- Dynamic selection of target columns
- Automatic data preprocessing using PyCaret
- User-friendly interface built with Vue.js
- Responsive design for optimal user experience
The application consists of two main components: the backend and the frontend.
- Backend: Built using FastAPI, the backend handles data uploads, processes the data, and returns predictions.
- Frontend: Developed with Vue.js, the frontend provides an interactive user interface for uploading files and displaying predictions.
To run this project, you'll need the following:
- Python 3.8 or higher
- Node.js 14 or higher
- FastAPI
- PyCaret
The backend is structured to handle data processing and predictions efficiently.
-
Navigate to the backend directory:
cd D:\DataPredictor\backend
-
Create a virtual environment and install dependencies:
python -m venv env # Activate the virtual environment: # Windows env\Scripts\activate # Linux/MacOS source env/bin/activate pip install -r requirements.txt
The frontend is designed to be responsive and user-friendly.
-
Navigate to the frontend directory:
cd D:\DataPredictor\frontend
-
Install the necessary Node.js packages:
npm install
To use the application, follow these steps:
-
Clone the repository
git clone https://github.com/pablosierrafernandez/DataPredictor.git
-
Set up the backend by following the instructions in the Backend with FastAPI section.
-
Set up the frontend by following the instructions in the Frontend with Vue.js section.
-
Start the backend server
uvicorn main:app --reload
-
Start the frontend development server
npm run serve
-
Access the application
Open your browser and navigate to
http://localhost:8080
to use the application.
Contributions are welcome! Please follow the contributing guidelines.
This project is licensed under the MIT License.
See the LICENSE
file for details.
- @pablosierrafernandez: Developer of the project.