Machine Learning Zuu
04/01/2026
We just wrapped up Week 02 of the Finetuning Sprint at the AI Engineer Essentials Bootcamp Zuu Crew AIπ
Most "Deep Learning" tutorials stop at trainer.train(). They show you a loss curve going down and call it a day. But in the real world, a model with a low loss is not a product. itβs just a file.
Yesterday, we didn't just finetune a model; we built a deployable Medical AI System.
Here is the engineering reality we covered:
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The Data Engine We moved beyond CSVs. We architected robust ChatML pipelines because "garbage in, garbage out" kills production apps.
β
The Hardware Hack We used QLoRA and 4-bit quantization to fit state-of-the-art models (Qwen 2.5) onto commodity hardware (Colab T4s). No A100s required.
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Real Evals We didn't rely on "Vibes" or exact-match metrics. We built an LLM-as-a-Judge pipeline to grade semantic accuracy.
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Safety & Guardrails We Red Teamed our own models. If a medical bot gives toxic advice, you are liable. We ensured ours refused harmful prompts systematically.
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Deployment We didn't leave the model in Python. We merged the adapters and exported to GGUF so it runs offline on a laptop using llama.cpp.
This isn't just about changing weights. Itβs about moving from being a Prompt Engineer to a Model Engineer.
Fun part is that this is just 5% of the curriculum. In the next 12 weeks, we are covering:
πΉ Context Engineering
πΉ Agentic RAG
πΉ Graph RAG
πΉ Observability
πΉ MCPs
πΉ LLMOps
πΉ Voice AI
Stop just jumping across notebooks. Start shipping products like a pro.
Enroll today if you want to be in the top 1% of AI Engineers in the island. π±π°
π zuucrew.ai
π +94 77 410 3273 (WhatsApp)
02/12/2025
Hope everyone in Sri Lanka is safe and holding up okay with this whole flood situation. π±π°π«Ά
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