Evaluating Hallucinations: How to Trust Your RAG System
Your AI sounds confident, but is it lying? A deeply technical guide on building automated 'LLM-as-a-judge' evaluation pipelines using the RAG Triad and Python.
Knowledge Hub
Industry insights, technical deep dives, and expert perspectives on Data, Cloud, and AI.
Evaluating Fine-Grained Performance in Custom LLMs
How do you know your model is 'good'? Moving beyond loss curves to semantic evaluation frameworks and 'LLM-as-a-Judge'.
Efficient PEFT Techniques: LoRA and QLoRA Explained
Training a 70B parameter model was once impossible for most. Low-Rank Adaptation (LoRA) changes the game, enabling training on consumer GPUs.
Governance at Scale: A Guide to Databricks Unity Catalog
The chaos of managing permissions in Databricks is over. Unity Catalog provides a centralised governance layer for all your data and AI assets.
Data Contracts: Stopping Microservices from Breaking Your Warehouse
Software engineers change database schemas; Data engineers cry. Learn how Data Contracts enforce an agreement between producers and consumers.
- · MLOps
Building Robust CI/CD Pipelines for Machine Learning
Bringing DevOps to Data Science. We explain how to automate training, testing, and deployment of ML models using GitHub Actions and Kubeflow.
