Enhance Business Value of Machine Learning Models by Integrating Machine Learning Ops (MLOps)

December 12, 9:00am, MST - 10:00am, MST




What you'll learn

As machine learning algorithms have advanced by leaps and bounds, the lack of standardized machine learning tools, frameworks and deployment practices remains a challenging task. This has resulted in low business value & usage of AI/ML models in production.

In this webinar, we will share our perspective on the need for standardization in the current machine learning lifecycle and discuss a comprehensive DevOps strategy for MLOps for organizations to successfully drive ML into production.

Key take-aways:

  • Need for MLOps in the machine learning lifecycle
  • Current challenges preventing organizations from successfully implementing enterprise ML in production
  • MLOps best practices and success stories
  • Collaborative tools available in the market to deploy predictive analytics solution
  • Security and compliance for MLOps in healthcare



Presented by:


Manisha Bafna

Asst. Vice President - Consulting


Daniel Dean

Cloud Solutions Architect