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How to Reduce ML Computing Costs: Building Efficient Multi-Cloud Infrastructure

Offered By: MLOps World: Machine Learning in Production via YouTube

Tags

MLOps Courses Machine Learning Courses Cloud Computing Courses Kubernetes Courses Terraform Courses Hybrid Cloud Courses Infrastructure Management Courses Cost Optimization Courses

Course Description

Overview

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Discover how to significantly reduce machine learning computing costs in this 38-minute conference talk from MLOps World. Learn from Jaeman An, Founder & CEO of VESSL AI, as he shares insights on building time- and cost-effective ML infrastructure. Explore hybrid cloud architectures using Terraform and Kubernetes, cost optimization techniques with spot instances and fractional GPUs, and solutions to common multi-environment challenges. Gain practical knowledge on dataset mounting, network performance optimization, and server monitoring. Follow a step-by-step guide to implement these strategies and potentially achieve over 80% cost savings on ML projects.

Syllabus

Intro
From notebooks to training jobs
Experiment dashboard
Cluster Dashboard
Multi-Cloud ML Infrastructure
Build hybrid cluster with Kubernetes & Terraform
Terraforming AWS Infrastructure
Test AWS Infrastructure
Terraforming GCP Infrastructure
Cloud Troubleshooting
Dataset Mounting
Cluster Management & Monitoring
Common Interface
Fractional GPUs
multicluster-scheduler
reCap: Step-by-Step Guide


Taught by

MLOps World: Machine Learning in Production

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