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PRANJUL RATHOUR
PRANJUL RATHOUR

Posted on Originally published at pranjulrathour.scult.in

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

#finetuning #transferlearning #terminology

'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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Presenting Annapurna on stage

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Talking through the products he has shipped

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Pitching at CSJMU, Kanpur

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At the VSICS podium, Kanpur

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:

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
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