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AI & MLOps

Train. Deploy. Monitor. Govern.

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AWS Resources

Official AWS documentation for AI & Machine Learning Operations

AWS

Amazon SageMaker

End-to-end ML platform

Official Docs →
AWS

Amazon Bedrock

Foundation models as a service

Official Docs →
AWS

AWS Rekognition

Computer vision service

Official Docs →
AWS

Amazon Comprehend

Natural language processing

Official Docs →
AWS

Amazon Kendra

Enterprise search with ML

Official Docs →
AWS

AWS Trainium

ML training accelerator

Official Docs →
AWS

Amazon Q

Generative AI assistant

Official Docs →
AWS

SageMaker Feature Store

ML feature management

Official Docs →

Azure Resources

Official Microsoft Azure documentation for AI & Machine Learning Operations

Azure

Azure Machine Learning

Enterprise ML platform

Official Docs →
Azure

Azure OpenAI Service

OpenAI models on Azure

Official Docs →
Azure

Azure AI Studio

AI development platform

Official Docs →
Azure

Azure Cognitive Services

Pre-built AI APIs

Official Docs →
Azure

Microsoft Fabric

Unified data and AI analytics

Official Docs →
Azure

Azure AI Search

AI-powered search service

Official Docs →
Azure

Copilot Studio

Custom copilot builder

Official Docs →
Azure

Azure Databricks

Unified data analytics platform

Official Docs →

GCP Resources

Official Google Cloud documentation for AI & Machine Learning Operations

GCP

Vertex AI

Unified ML platform

Official Docs →
GCP

Google Gemini API

Google's multimodal AI model

Official Docs →
GCP

BigQuery ML

ML in SQL at scale

Official Docs →
GCP

Vertex AI Workbench

Managed Jupyter notebooks

Official Docs →
GCP

Document AI

Intelligent document processing

Official Docs →
GCP

Vertex AI Model Garden

Model discovery and deployment

Official Docs →
GCP

Duet AI for Developers

AI coding assistant for GCP

Official Docs →
GCP

AlloyDB AI

Vector search in PostgreSQL

Official Docs →

Featured Articles

In-depth technical blog posts on AI & Machine Learning Operations

BLOG POST 01

Building Production RAG Systems on AWS Bedrock

Knowledge Bases, embeddings, vector search, and Bedrock Guardrails for enterprise RAG

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BLOG POST 02

MLOps with Amazon SageMaker: Full Pipeline from Data to Production

SageMaker Pipelines, Model Registry, Model Monitor, and deployment strategies

Read article →
BLOG POST 03

Azure Machine Learning: Enterprise MLOps at Microsoft Scale

Workspaces, pipelines, Responsible AI dashboard, and Azure OpenAI integration

Read article →
View All 10 Articles →