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07:21
2026-06-22
dev.to
machine-learning

How to Deploy Your ML Model to AWS (Step-by-Step Guide)

A developer provides a step-by-step guide to deploying machine learning models to AWS using SageMaker, covering model packaging, S3 upload, endpoint creation, and inference testing. The guide includes…

04:00
2026-06-19
dev.to
developer-tools

Stop Saying "It Works on My Machine": Docker for AI Engineers

Docker solves the 'it works on my machine' problem for AI engineers by packaging all dependencies—OS, Python, packages, code, and config—into a single portable image. A typical AI project has multiple…

20:29
2026-06-06
dev.to
ai-infrastructure

Closing the execution gap, Part 2: Dependency management

Jhansi.io v0.3 introduces persistent dependency management for AI-generated code, eliminating the need for manual package installation in cloud sandboxes. The update automatically installs dependencie…

12:35
2026-06-03
dev.to
machine-learning

Day 4: Create a Standard ML Project Structure

A developer at xFusionCorp Industries restructured a fraud-detection machine learning project at `/root/code/fraud-detection/` to match the company's standard layout. The project now includes director…

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