The amazing Byron Allen talks to us about why MLflow and Kubeflow are not playing the same game! ML flow vs Kubeflow is more like comparing apples to oranges or as he likes to make the analogy they are both cheese but one is an all-rounder and the other a high-class delicacy. This can be quite deceiving when analyzing the two. We do a deep dive into the functionalities of both and the pros/cons they have to offer.
In this episode
AI & ML Practice Lead, Contino
Byron wears several hats. AI & ML practice lead, solutions architect, ML engineer, data engineer, data scientist, Google Cloud Authorized Trainer, and scrum master. He has a track record of successfully advising on and delivering data science platforms and projects. Byron has a mix of technical capability, business acumen, and communication skills that make me an effective leader, team player, and technology advocate. See Byron write at https://firstname.lastname@example.org
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.
George attained his Bachelors in Physics from the University of Birmingham in 2019, his final year project in Medical Imaging investigated a low radiation alternative to Gamma Cameras for use in tumour imaging. George believes advances in AI will lead to improvements in the quality and speed of healthcare, freeing up resources for complex cases and preventative medicine in the process. He will be working within our Research and Development team focusing on the key areas of clinical data and increasing the efficiency of research as Behold.ai continues to innovate.