Introduction: Fine-tuning transforms general-purpose LLMs into specialized models that excel at your specific tasks. While prompting can get you far, fine-tuning unlocks capabilities that prompting alone cannot achieve: consistent output formats, domain-specific knowledge, reduced latency from shorter prompts, and behavior that would require extensive few-shot examples. This guide covers the practical aspects of LLM fine-tuning: […]
Read more →Category: Emerging Technologies
Emerging technologies include a variety of technologies such as educational technology, information technology, nanotechnology, biotechnology, cognitive science, psychotechnology, robotics, and artificial intelligence.
Private Kubernetes cluster in AKS with Azure Private Link
Today, we’ll take a look at a new feature in AKS called Azure Private Link, which allows you to connect to AKS securely and privately over the Microsoft Azure backbone network. In the past, connecting to AKS from an on-premises network or other virtual network required using a public IP address, which posed potential security […]
Read more →Building GDPR-Compliant FHIR APIs: A European Healthcare Guide
Executive Summary Building FHIR REST APIs in the European Union requires strict compliance with GDPR Article 9 for processing health data (special category personal data). This comprehensive guide provides solution architects and developers with production-ready patterns for implementing GDPR-compliant FHIR APIs, covering encryption, consent management, access controls, audit logging, and data subject rights. 🏥 HEALTHCARE […]
Read more →Mastering GKE: A Deep Dive into Google Kubernetes Engine for Production Workloads
Introduction: Google Kubernetes Engine represents the gold standard for managed Kubernetes, built on the same infrastructure that runs Google’s own containerized workloads at massive scale. This deep dive explores GKE’s enterprise capabilities—from Autopilot mode that eliminates node management to advanced features like workload identity, binary authorization, and multi-cluster service mesh. After deploying production Kubernetes clusters […]
Read more →Running LLMs on Kubernetes: Production Deployment Guide
Deploying LLMs on Kubernetes requires careful planning. After deploying 25+ LLM models on Kubernetes, I’ve learned what works. Here’s the complete guide to running LLMs on Kubernetes in production. Figure 1: Kubernetes LLM Architecture Why Kubernetes for LLMs Kubernetes offers significant advantages for LLM deployment: Scalability: Auto-scale based on demand Resource management: Efficient GPU and […]
Read more →Types of Machine Learning Explained: Supervised, Unsupervised, and Reinforcement Learning
Deep dive into the three fundamental paradigms of machine learning. Explore supervised learning for predictions, unsupervised learning for pattern discovery, and reinforcement learning for decision optimization with practical Python examples.
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