What is MLOps?

MLOps is a set of software development practices that aims to build, deploy, monitor and maintain ML/AI (Machine Learning/Artificial Intelligence) models in production reliably and efficiently.  

The term is derived from a contraction of machine learning and the continuous development practices of DevOps.

Ultra Tendency and MLOps

• Ultra Tendency can guide your teams through the many different features, algorithms, modeling techniques, and parameter configurations to find what works to address your problems.  

• The challenge of tracking what worked and what didn't while maintaining reproducibility is much larger than traditional software engineering.  

• We can develop tools and processes to ensure less waste in repeated experiments while maintaining code reusability. 

Challenges with ML Ops 

• Deployment of ML/AI models 

• Integration of ML/AI models into software and hardware technology 

• Automation of deployment procedures 

• Reproducibility of data, models, and predictions 

• Diagnostics 

• Governance and regulatory compliance 

• Scalability 

• Collaboration 

• Monitoring and management 

• Business uses 

• Iterative progression of ML/AI development 

A tricky element of ML Ops is that ML/AI is much more experimental than traditional software engineering.