# Deep Learning & NLP

Transformers, BERT, LLM applications, text preprocessing, and LoRA fine-tuning.

Use this subtrack when you want portfolio-style NLP and LLM projects inside a practical workflow, rather than a deep theory-first treatment.

## How To Use This Subtrack Well

- Start with one concrete language task before mixing prompting, fine-tuning, and retrieval together.
- Compare simple baselines against heavier model adaptation so the project stays disciplined.
- Pair this subtrack with [../../12-llm-finetuning/README.md](../../12-llm-finetuning/README.md) and [../../08-rag/README.md](../../08-rag/README.md) as needed.

## What Comes Next

- Continue to [../README.md](../README.md) for the broader practical data science roadmap.
- Continue to [../../12-llm-finetuning/README.md](../../12-llm-finetuning/README.md) if the project points toward model adaptation.
- Continue to [../../15-ai-agents/README.md](../../15-ai-agents/README.md) if you want to turn the language workflows into tool-using systems.
