Composing data to extract features can be a significant problem Key factors are the data size, compliance restrictions, and real-time data Ethics (and law) can drive extremely complex audit requirements In the cloud, you can do anything - at a price.
In this episode
Chief Data Scientist, LexisNexis Risk Solutions
One of the creators of the world's first big data platform (HPCC); David has been tackling big data problems for two decades. A mathematician, compiler writer, and data sponge with more than five dozen patents spanning platforms linking, and search. Most inventors think outside the box; David can't even remember where the box is. He leads the team that creates their core Data Science methods used by hundreds of data scientists.
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.