IBM Journey to AI blog

AUGUST 12, 2024

Primary activities AIOps relies on big data-driven analytics , ML algorithms and other AI-driven techniques to continuously track and analyze ITOps data. The process includes activities such as anomaly detection, event correlation, predictive analytics, automated root cause analysis and natural language processing (NLP).

Big Data 266

Big Data DevOps Automation Machine Learning 266

ODSC - Open Data Science

JULY 19, 2023

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.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

Snorkel AI

JULY 5, 2023

RC : I have had ML engineers tell me, “You didn’t need to do feature selection anymore, and that you could just throw everything at the model and it will figure out what to keep and what to throw away.” That’s where you start to see data drift. So does that mean feature selection is no longer necessary?

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

AWS Machine Learning Blog

DECEMBER 4, 2024

Available in SageMaker AI and SageMaker Unified Studio (preview) Data scientists and ML engineers can access these applications from Amazon SageMaker AI (formerly known as Amazon SageMaker) and from SageMaker Unified Studio. Comet has been trusted by enterprise customers and academic teams since 2017.

ML 132

ML Generative AI Data Scientist ML Engineer 132