ML Ops

Machine Learning Operations

  • 22301
  • 27001
  • 9001

With a high level of expertise in ML Ops, Ultra Tendency can support customers in their journey to embrace cutting edge applications of ML/AI technology. ML Ops 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 (Developer Operations).

In ML Ops, ML/AI models are tested and developed in isolated systems, until operating at an acceptable effectiveness. With Ultra Tendency ML Ops services, we will improve automation in your IT services and increase the quality of production models, while also focusing on business and regulatory requirements. Ultra Tendency ML Ops applies to the entire lifecycle, from integration with model generation, including the software development lifecycle, and continuous integration/continuous delivery, orchestration, and deployment, to health, diagnostics, governance, and business metrics.

There are many challenges that ML Ops addresses for an organisation, including:

  • 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. Ultra Tendency can guide your teams through the many different features, algorithms, modelling 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. Ultra Tendency can develop tools and processes must to ensure less waste in repeated experiments while maintaining code reusability.

With years of experience migrating teams into an ML Ops environment, Ultra Tendency can assist in putting into place long lasting and successful ML Ops. By starting with Ultra Tendency on deploying your ML/AI models, you can be certain that the ML Ops deployed at your organization will grow and adopt to meet all of your business’s needs.

References