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Niketkumardheeryan / ML-CaPsule

ML-capsule is a Project for beginners and experienced data science Enthusiasts who don't have a mentor or guidance and wish to learn Machine learning. Using our repo they can learn ML, DL, and many related technologies with different real-world projects and become Interview ready.
MIT License
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Feature Request: News Articles Category Prediction #1102

Open pratikwayal01 opened 3 days ago

pratikwayal01 commented 3 days ago

Feature Request: News Articles Category Prediction

Summary: A feature to predict the category of a news article (such as Sports, Politics, Entertainment, Technology, etc.) based on its content. This will enhance the platform's ability to automatically categorize news content and make it easier for users to find relevant articles.

Details:

  1. Objective: Implement a model that can predict the category of a news article using its text. The model should be able to handle various article topics and assign categories like:

    • Politics
    • Sports
    • Entertainment
    • Technology
    • Science
    • Health
    • Business
    • World

  2. Requirements:

    • A dataset of categorized news articles for training the model.
    • A pre-trained Natural Language Processing (NLP) model for text classification (such as BERT, GPT, or similar models).
    • Ability to integrate the model with the existing backend, ensuring real-time predictions when new articles are uploaded or written.

  3. Proposed Approach:

    • Preprocess the articles by removing unnecessary metadata, cleaning text, and tokenization.
    • Train an NLP-based classifier (e.g., Logistic Regression, Random Forest, or a deep learning model like a Transformer) on the labeled dataset of news articles.
    • Evaluate the model’s accuracy using standard metrics like F1-score, precision, and recall.
    • Integrate the trained model into the system, enabling automatic categorization of articles at the time of submission.
    • Provide an API for querying the model to get category predictions.

  4. Benefits:

    • Improves user experience by categorizing articles accurately and automatically.
    • Enhances the discoverability of news articles based on categories.
    • Reduces manual effort in tagging and organizing articles.

  5. Possible Challenges:

    • Data availability: Large and diverse datasets are required for accurate prediction across multiple categories.
    • Handling ambiguous content that may fit into multiple categories.
github-actions[bot] commented 3 days ago

Thanks for creating the issue,Please read the Pinned issued first and Readme.md in each Pull Request you made. Keep learning...

Niketkumardheeryan commented 3 days ago

go for it

pratikwayal01 commented 3 days ago

thanks @Niketkumardheeryan

ReaganBlade commented 3 days ago

Hello @Niketkumardheeryan I'm working on some classification Projects, So I would Like to work on this issue. Can you please assign it to me?