MLOps: Monitoring and Managing Drift
Editor’s note: Oliver Zeigermann is a speaker for ODSC West 2023 this Fall. Be sure to check out his talk, “MLOps: Monitoring and Managing Drift,” there! The trouble with machine learning starts after you put your model into production.  Typically, you want to bring something into... Read more
Machine Learning Operations (MLOPs) with Azure Machine Learning
Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team. The data... Read more
8 Data Lake Vendors to Make Your Data Life Easier in 2023
Data has to be stored somewhere. Data warehouses are repositories for your cleaned, processed data, but what about all that unstructured data your organization is starting to notice? Where does it go? To make your data management processes easier, here’s a primer on data lakes, and... Read more
How MLOps Work in the Era of Large Language Models
Large language models (LLMs) and generative AI have taken the world by storm, allowing AI to enter the mainstream and show that AI is real and here to stay. However, a new paradigm has entered the chat, as LLMs don’t follow the same rules and expectations... Read more
Solve Your MLOps Problems with an Open Source Data Science Stack
Editor’s note: Dean Pleban is a speaker for ODSC East 2023. Be sure to check out his talk, “Solving MLOps from First Principles,” there! Data scientists have challenges and need tools to overcome them. It’s best to use open-source, best-of-breed, modular solutions. It’s also a good... Read more
Things Data Scientists Should Know About Productionizing Machine Learning
It is often too much to ask for the data scientist to become a domain expert. However, in all cases the data scientist must develop strong domain empathy to help define and solve the right problems. –  Nina Zumel and John Mount, Practical Data Science with... Read more
MLOps V2 Solution Accelerator – Unifying MLOps at Microsoft
Article by Scott Donohoo and Setu Chokshi of Microsoft. MLOps means different things to different people, however, the fundamental essence of MLOps is to deliver models into productions faster with a consistent, repeatable, and reliable approach. Machine Learning Operations (MLOps) is key to accelerating how data... Read more
MLOps for Musicians
Editor’s note: Akira is a speaker for ODSC APAC this September 7th-8th. Be sure to check out his talk, “MLOps for Musicians,” there! Just 5 years ago, thinking about how to deploy and reliably run AI models in a critical operation, known as MLOps, seemed like... Read more
A Brief History of MLOps
Data is becoming more complex, and so are the approaches designed to process it. Companies have access to more data than ever, but many still struggle to glean the full potential of insights from what they have. Machine learning has stepped in to fill the gap.... Read more
10 Trending Virtual MLOps Talks Coming to ODSC Europe 2022
A model that never makes it into production is one that is incapable of producing value for a business or organization. Unfortunately, the percentage of models that make it out of development is still low. However, the field of MLOps is focused on this very problem... Read more