[Enhancement]: Add Multilingual & Indian Language NLP Resources

[AG141293]

🔍 Description

The NLP section currently has no resources for multilingual NLP.
or Indian language processing, which is a major and growing field,
especially in India.

📌 Current Behavior

The nlp/ section and README have no Indian language or
multilingual NLP resources listed.

✅ Suggested Addition

Add under the NLP section:

• AI4Bharat (https://ai4bharat.iitm.ac.in) — Indian language NLP models
• IndicNLP Library (https://github.com/anoopkunchukuttan/indic_nlp_library) — NLP tools for Indian languages
• Samanantar Dataset — largest publicly available parallel corpus for Indian languages
• Bhashini (https://bhashini.gov.in) — Government of India multilingual AI platform

💡 Why This Matters

India has 22 official languages. Multilingual NLP is one of the
fastest-growing niches in AI. This repo serves many Indian
contributors and students who would directly benefit from
these resources.

🙋 Contribution

I have hands-on experience building multilingual NLP pipelines.
handling 10,000+ dialect variations during my ML internship.
I can submit a PR for this if assigned.

[github-actions]

Thank you for creating this issue! 🎉 We'll look into it as soon as possible. In the meantime, please make sure to provide all the necessary details and context. If you have any questions reach out to LinkedIn. Your contributions are highly appreciated! 😊

Note: I Maintain the repo issue twice a day, or ideally 1 day, If your issue goes stale for more than one day you can tag and comment on this same issue.

You can also check our CONTRIBUTING.md for guidelines on contributing to this project.
We are here to help you on this journey of opensource, any help feel free to tag me or book an appointment.

[AG141293]

Thank you for the quick response! 🙏

I have gone through the CONTRIBUTING.md guidelines, and I am ready to work on this.

Could you please assign this issue to me so I can submit a PR?

Here's my plan for the PR:

• Add AI4Bharat, IndicNLP Library, Samanantar Dataset, and Bhashini
  under the NLP section in the README
• Follow the existing formatting style of the repo
• Keep it clean and beginner-friendly

I have hands-on experience with multilingual NLP pipelines from my
internship at Tech Mahindra Makers Lab, so I can add quality
descriptions for each resource. 🚀