Closed Omarelsherif010 closed 1 year ago
From this video I find a summary of MLOps tools ( Important tools:
resources: DTC-MLOps youtube video
There are two ways for creating MLOps products:
1. Using open-source MLOps software for each step
Experiment Tracking and Model Metadata Management Tools These tools allow you to manage model metadata and help with experiment tracking
Orchestration and Workflow Pipelines MLOps Tools help you create data science projects and manage machine learning workflows
Data and Pipeline Versioning Tools With these MLOps tools, you can manage tasks around data and pipeline versioning
Model Deployment and Serving Tools
Model Monitoring in Production ML Ops Tools Whether your ML model is in development, validation, or deployed to production, these tools can help you monitor a range of factors
2. Using End-to-End MLOps Platforms
Resources:
Example of End-to-End MLOps project
@amr-atif @anasos20 Have a look on this link and this image
that looks good Ahmed very useful @ahmedtarek26
@ahmedtarek26 Provide a word file and push it to the Doc folder in our repo Great Work BTW keep going ❤️
@anasos20 I'll do it now
Your assistant in this task is @Omarelsherif010
We need to know common MLOps tools available inside the developer student pack and free tools. We need to know the role of every tool and where it is in the circle