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MaiBERT

NewsPortal with BERT-powered Backend

Welcome to MaiBERT, a NewsPortal project powered by BERT for backend operations. MaiBERT is designed to provide an efficient and intuitive platform for news consumption, with features including news fetching, classification, and translation. With its robust backend powered by BERT, MaiBERT offers accurate and dynamic news categorization across 10 different classes.

Introduction

MaiBERT is developed as a culmination of efforts towards completing a major project. The project utilizes a stack comprising React.js, Bootstrap, and CSS to create a seamless and engaging user interface, ensuring a smooth and enjoyable user experience.

Features

  1. BERT-powered Backend: MaiBERT leverages the power of BERT (Bidirectional Encoder Representations from Transformers) for its backend operations, ensuring precise and efficient news classification.
  2. News Fetching: The platform is equipped to fetch news articles from various sources, providing users with a diverse selection of content.
  3. Classification: MaiBERT employs advanced classification techniques to categorize news articles into 10 different classes, facilitating easy navigation and access to relevant content.
  4. Translation: With built-in translation features, MaiBERT enables users to access news articles in multiple languages, breaking down language barriers and promoting inclusivity.
  5. User-friendly Interface: Developed with React.js, Bootstrap, and CSS, MaiBERT boasts a user-friendly interface designed to enhance usability and accessibility.

Getting Started

To get started with MaiBERT, follow these steps:

Clone the Repository:

Clone the MaiBERT repository from GitHub to your local machine.

Install Dependencies:

Navigate to the project directory and install the necessary dependencies using npm or yarn.

npm install

Run the Application:

Start the application locally using npm or yarn.

npm start

Explore MaiBERT: Access MaiBERT through your preferred web browser and start exploring the latest news articles across various categories.

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