Photo by Markus Winkler on Unsplash Machine Learning (ML) has a number of applications in modern commerce, with Information Retrieval (IR) being one of the most common. Many e-businesses use it to gauge search quality relevance on their platforms to provide better...

Iguazio’s Data Scientist discusses how to detect and handle problems that arise when models lose their accuracy and how to implement concept drift detection and remediation in production. He shows how to automate MLOps processes at scale, to handle drift detection...

In the last decade, significant technological progress has been driven rapidly by numerous advances in applications of machine learning. Novel ML techniques have revolutionized industries by cracking historically elusive problems in computer vision, natural language...

Introduction In the world of computer vision, accuracy is critical. If your model isn’t detecting images correctly, then its application in the real world can be rendered useless, or worse, dangerous. A computer vision model that incorrectly identifies objects can...

David Aronchick, Head of OSS ML Strategy at Microsoft, Marvin Buss, Azure Customer Engineer at Microsoft, and Zander Matheson, Senior Data Scientist at Github discuss using Git to enable continuous delivery of machine learning to production, enable controlled...

Generate synthetic sequential data with TimeGAN Time-series or sequential data can be defined as any data that has time dependency. Cool, huh, but where can I find sequential data? Well, a bit everywhere, from credit card transactions, my everyday...