Machine Learning

Iguazio Product tutorial 2021

The Iguazio Data Science Platform enables you to develop, deploy and manage real-time AI applications at scale. It provides data science, data engineering and DevOps teams with one platform to operationalize machine learning and rapidly deploy operational ML pipelines. The platform includes an online and offline feature store, fully integrated with automated model monitoring and drift detection, model serving and dynamic scaling capabilities, all packaged in an open and managed platform.

Fast Forward Live: Session-based Recommender Systems

Join us live with Fast Forward Labs to discuss the recently possible in Machine Learning and AI. Being able to recommend an item of interest to a user (based on their past preferences) is a highly relevant problem in practice. A key trend over the past few years has been session-based recommendation algorithms that provide recommendations solely based on a user’s interactions in an ongoing session, and which do not require the existence of user profiles or their entire historical preferences. This report explores a simple, yet powerful, NLP-based approach (word2vec) to recommend a next item to a user. While NLP-based approaches are generally employed for linguistic tasks, here we exploit them to learn the structure induced by a user’s behavior or an item’s nature.

Cerner depends on Elastic machine learning for a healthy infrastructure

Cerner Corp. is a supplier of healthcare information technology systems, services, and devices. The company, with $5.7 billion in annual revenue, empowers people and communities to engage in their own care. A key aspect of the business is surfacing data to enable their clients to make informed decisions about their healthcare. The 29,000 Cerner employees in 30 countries are on a mission to shape the healthcare of tomorrow.


Ways AI is Driving More Efficient Application Performance Monitoring

In the digital age, the speed and performance of apps and websites have a huge impact on the customer experience. To ensure a high level of quality, Application Performance Monitoring (APM) refers to the process of tracking the performance and availability of software systems. Let’s look at what Application Performance Monitoring is, how AI and machine learning are being applied to stay ahead of the competition, and several real-world use cases.

Simplifying MLOps with model-driven operators

In early markets such as MLOps, solutions to parts of a large problem arise from multiple open source communities, startups and industry leaders. For the consumer, this entails one problem - integrating pieces of a software puzzle in a maintainable way. Model-driven operators promise a solution by connecting the ops of a single application with declarative integration in a standard that empowers providers.