Welcome to our collection of articles on the topic of integrated deployment, where we focus on solving the challenges around productionizing Data Science. So far, in this collection we have introduced the topic of integrated deployment, discussed the topics of continuous deployment and automated machine learning, and presented the autoML verified component. In today’s article, we would like to […]
Integrated Deployment: Continuous Deployment
Click to learn more about author Paolo Tamagnini. In this second article of our integrated deployment blog series – where we focus on solving the challenges around productionizing Data Science – we look at the model part of the process. In the previous article we covered a simple integrated deployment use case. We first looked at an existing […]
An Introduction to Integrated Deployment
Click to learn more about author Paolo Tamagnini. Welcome our integrated deployment blog series, where we focus on solving the challenges around productionizing Data Science. Topics will include: Resolving the challenges of deploying models Building guided analytics applications that create not only a model but a complete model process, using our component approach to AutoML […]
KNIME Launches Integrated Deployment
According to a new press release, “KNIME today unveiled a groundbreaking approach — Integrated Deployment — to eliminate the gap between the creation of data science models and their use in production. Integrated Deployment allows not just a model but all of its associated preparation and post-process steps to be identified and automatically reused in […]