Organizations rely on machine learning engineers (MLEs) to operationalize ML, i.e., deploy and maintain ML pipelines in production. The process of operationalizing ML, or MLOps, consists of a continual loop of (i) data collection and labeling, (ii) experi... (more…)

There are dangers in having models running the world and making decisions from hiring to criminal justice... (more…)

Machine Learning APIs can be integrated into your company and boost your business performance. Here’s why you can benefit from them. (more…)

This blog post introduces several improvements to PySpark that facilitate the development of custom ML algorithms and 3rd-party ML packages using Python. After introducing the main algorithm APIs in MLlib, we discuss current challenges in building custom ... (more…)

Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning. This article discusses where links have been and should be establishe... (more…)