AI / Machine Learning in 30 days(IQi30) : 5-Wk Implementation
Spyglass’ AI / Machine Learning in 30 Days (IQi30) is a 5-Week Implementation designed to help you create a Machine Learning solution in Azure quickly and efficiently.
Spyglass’ AI / Machine Learning in 30 Days (IQi30) is a 5-Week Implementation designed to help you create a Machine Learning solution in Azure quickly and efficiently. Our approach deploys a secure Azure Machine Learning environment, leveraging Azure Well-Architected and the Cloud Adoption Framework. With a Prebuilt Azure Blueprint for secure platform deployment, deploying a ML or AI solution is quick and easy. With dozens of prebuilt templates, code bases, tool kit and other assets to leverage, your ML program will be up and running quickly!
We leverage our Azure Blueprint Solution Accelerator for Analytics (IQi30) to implement the analytics workload & integrate with your Azure IT services. Our complete package includes a toolkit for Azure ML, workshops to educate and envisioning sessions which place ML within your business world fit to yours and industry use-cases.
Azure AI Platform Overview
Azure ML Services Overview
Auto ML & Designer
Working with Azure ML
Implementing a Model Deployment
STAGE 1 - Strategy & Plan (Wk 1): Stakeholder identification, Total Cost of Ownership Assessment for Azure Services, Project Schedule review, Requirements gathering, Platform & Blueprint planning.
STAGE 2 – Ready (Wk 2-3): Data & AI Architecture workshop, Build & Implement Azure ML Landing Zone, ML Workshops 1 & 2.
STAGE 3- Innovate (Wk 4): Review modeling requirements, performance and accuracy definitions, data source identification, feature selection and engineering, model training and review, sketch and envision future use-cases, ML Workshops 3 & 4 and build agenda for production planning.
STAGE 4 – Accelerate (Wk 5): Review solution proof-of-concept report, get feedback, and roadmap production adoption. Technical KT & User Sessions, ML Workshops 5, Final Project Review & Sign Off.
DELIVERABLES- Spyglass will deliver a full Machine Learning platform, roadmap, and workload proof-of-concept in 30 working days/5 weeks for a fixed fee of $55k.