We all are familiar with the concept of MVP. In the world of DevOps, one is also familiar with Minimal Viable Feature and further Minimal Viable change. CI/CD is the orchestrator and the underlying base to enable automated experimentation, to start small, and build an idea for production. Now if we use the same fundamentals in MLOps, what does that mean? The podcast will take the audience on a journey in understanding the fundamentals of orchestrating machine predictions using responsible CI/CD in MLOps in this ever-changing, agile world of software development. One shall hope to learn how to excel at the craft of CI for Machine Learning (ML), lowering the cost of deployment through a robust CI/CD/CT/CF framework.
In this episode
MLOPS Advisor, Gitlab
Monmayuri is an advisor, data scientist, and researcher specializing in MLops/DevOps at GitLab in Sydney. She builds creative, products to solve challenges for companies in industries as diverse as financial services, healthcare, and human capital. Along the way, Mon has built expertise in Natural Language Processing, scalable feature engineering, MLOps transformation and digitization, and the humanization of technology. With a background in applied mathematics in biomedical engineering, she likes to describe the essence of AI as “low-cost prediction” and MLOps as “low-cost transaction” and believes the world needs the collaboration of poets, historians, artists, psychoanalysts and scientists, engineers to unlock the potential of these emerging technologies where one works in making a machine think like humans and be efficient automated fortune tellers.
Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.
Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.