A practical, end-to-end tutorial on instruction tuning LLMs: data design, LoRA/QLoRA training code, evaluation, deployment, and production tips.
Design and ship a production-grade AI auto-tagging classification API: models, thresholds, architecture, evaluation, security, and scaling best practices.
Build, deploy, and scale a production-ready AI text classification API with Python and FastAPI—training, serving, security, metrics, and monitoring.
A step-by-step LoRA fine-tuning guide with theory, setup, classic LoRA and QLoRA code, evaluation, merging, and practical tips.
How to integrate AI sentiment analysis APIs into social media stacks—architecture, metrics, sample code, and best practices for reliable, real-time insights.
A step-by-step guide to preparing high-quality datasets for LLM fine-tuning, from sourcing and cleaning to formats, safety, splits, and evaluation.
