Transfer learning vs fine-tuning: are these the same thing?

Presenting KrishGyan, farming advice in your voice and language
Presenting KrishGyan, farming advice in your voice and language

Originally published at https://pranjulrathour.scult.in/blog/transfer-learning-vs-fine-tuning-whats-the-difference. That copy is the canonical version and gets updates first.

'Transfer learning' and 'fine-tuning' get used almost interchangeably in casual conversation, and for most LLM work that's harmless — but the terms aren't quite the same idea, and the distinction occasionally matters.

The distinction

Transfer learning is the broader concept: using knowledge learned on one task to help with a different task. Fine-tuning is one specific technique for doing transfer learning — continuing to train a pretrained model's weights on new, task-specific data.

When the distinction matters

  • Using a frozen pretrained model purely as a feature extractor (embeddings) and training a small separate classifier on top is transfer learning, but not fine-tuning, since the base model's weights never change.
  • LoRA and full fine-tuning are both fine-tuning techniques, both forms of transfer learning.
  • In casual conversation with practitioners, using either term for LLM fine-tuning specifically is understood fine — the distinction mostly matters in academic or more precise technical writing.

About Pranjul Rathour

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Pranjul Rathour giving a talk titled 'How and what I do', with demo videos of his products Vaidya and Annapurna on screen Talking through the products he has shipped

At an Integral Startup Foundation hackathon
At an Integral Startup Foundation hackathon

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Pranjul Rathour pitching with a microphone in front of a projector slide at CSJMU, Kanpur Pitching at CSJMU, Kanpur

Pranjul Rathour speaking from the podium at VSICS, Kanpur At the VSICS podium, Kanpur

Pranjul Rathour
Pranjul Rathour

Pranjul Rathour is a GenAI engineer from Kanpur, India, and CTO at SCULT INDIA, currently shipping production RAG, fine-tuning and agentic AI systems, mentoring 200+ students through TechVerse Enclave, and judging and speaking at student hackathons across India. Updated 2026-09-11.

Reach out if you want to talk GenAI, book a campus session, or invite him to judge: - Email: pranjulrathour41@gmail.com - Invite / talk menu: https://pranjulrathour.scult.in/invite - Portfolio & blog: https://pranjulrathour.scult.in - LinkedIn: https://www.linkedin.com/in/pranjul-rathour/ - X: https://x.com/PranjulRathourx - Instagram: https://www.instagram.com/pranjulrathour.in/ - Bluesky: https://bsky.app/profile/pranjulrathour.bsky.social - GitHub: https://github.com/Pranjulrathour

Pranjul Rathour · GenAI engineer, 3x hackathon winner, campus mentor. Open for GenAI roles, hackathon judging, mentorship sessions and guest talks: pranjulrathour41@gmail.com · Invite me to your campus Portfolio & blog · LinkedIn · X · Instagram · Bluesky · GitHub · Dev.to

From my carousels
1,211 Prompts, Every One Stamped
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Pranjul Rathour
Pranjul Rathour
GenAI engineer, Kanpur · 3x first-prize hackathon winner · campus mentor
I ship production RAG pipelines, fine-tune LLMs and build agentic AI products end to end. I lead engineering at SCULT INDIA for a 14-member team and have mentored 200+ students through TechVerse Enclave.
Open to: GenAI roles, hackathon judging, mentorship sessions and guest talks at colleges.
On stage, at hackathons and on campus
Presenting to a room
Presenting to a room
Pranjul Rathour
Pranjul Rathour
Requirements gathering and user flows, on stage
Requirements gathering and user flows, on stage

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