Use table partitioning to dramatically speed up queries on large datasets.
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Building Interoperable Healthcare Data Systems for AI: A Complete Guide to FHIR, Standards, and Governance
Healthcare AI fails when data remains siloed. This article explores how FHIR, SNOMED CT, and platform thinking enable interoperable healthcare data systems for AI at scale, with insights from EU, UK, and Ireland initiatives.
Read more →Tips and Tricks – Use Window Functions for Running Calculations
Calculate running totals, rankings, and moving averages efficiently with SQL window functions.
Read more →Data Quality for AI: Ensuring High-Quality Training Data
Data quality determines AI model performance. After managing data quality for 100+ AI projects, I’ve learned what matters. Here’s the complete guide to ensuring high-quality training data. Figure 1: Data Quality Framework Why Data Quality Matters Data quality directly impacts model performance: Accuracy: Poor data leads to poor predictions Bias: Biased data creates biased models […]
Read more →Production Model Deployment Patterns: From REST APIs to Kubernetes Orchestration in Python
After deploying hundreds of ML models to production across startups and enterprises, I’ve learned that model deployment is where most AI projects fail. Not because the models don’t work—but because teams underestimate the engineering complexity of serving predictions reliably at scale. This article shares production-tested deployment patterns from REST APIs to Kubernetes orchestration. 1. The […]
Read more →Mastering LangChain: The Complete Getting Started Guide to Building Production LLM Applications
Introduction: LangChain has emerged as the de facto standard framework for building applications powered by large language models. Originally released in October 2022, it has grown from a simple prompt chaining library into a comprehensive ecosystem that includes LangChain Core, LangChain Community, LangGraph, and LangSmith. With over 90,000 GitHub stars and adoption by thousands of […]
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