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Enterprise Monitoring Landscape – Overview and New Entrants

This post covers the complete Enterprise Monitoring landscape including the newest category of artificial intelligence and machine learning monitoring. With the advent and adoption of web products and services over the past two decades, an entire category of systems dedicated to managing the related infrastructure has developed. Software monitoring, one of the core operational needs, … Continue reading “Enterprise Monitoring Landscape – Overview and New Entrants”

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Explainable Monitoring: Stop flying blind and monitor your AI

Data Science teams find Explainable Monitoring essential to manage their AI. Photo by Bruce Warrington on Unsplash The Need for AI/ML Monitoring We’re living in unprecedented times where in a matter of a few weeks, things changed dramatically for many humans and businesses across the globe. With COVID-19 spreading its wings across the globe, and … Continue reading “Explainable Monitoring: Stop flying blind and monitor your AI”

Welcome Pranil Dasika!

We’re stoked to introduce Pranil Dasika, the newest member of our team. Pranil joined us as a Principal Software Engineer in the midst of COVID-19 pandemic and recently stepped up as our Head of Engineering. Before joining Fiddler Labs, Pranil had played key engineering roles at early and growth-stage startups, both in consumer and enterprise … Continue reading “Welcome Pranil Dasika!”

Identifying bias when sensitive attribute data is unavailable: Geolocation in Mortgage Data

In our last post, we explored data on mortgage applicants from 2017 released in accordance with the Home Mortgage Disclosure Act (HMDA). We will use that data, which includes self-reported race of applicants, to test how well we can infer race using applicants’ geolocations in our effort to better understand methods to infer missing sensitive … Continue reading “Identifying bias when sensitive attribute data is unavailable: Geolocation in Mortgage Data”

Explainable Churn Analysis with MemSQL and Fiddler

Fiddler and MemSQL are partnering to offer the power of MemSQL to users of Fiddler’s toolset for explainable AI – and to offer Fiddler’s explainability tools to the many MemSQL customers who are already using, or moving to operational AI. To this end, the two companies are offering new, efficient ways to connect MemSQL self-managed … Continue reading “Explainable Churn Analysis with MemSQL and Fiddler”

Identifying bias when sensitive attribute data is unavailable: Exploring Data from the HMDA

To test their automated systems for possible bias across racial or gender lines, organizations may seek to know which individuals belong to each race and gender group. However, such information may not be easily accessible, and organizations may use techniques to infer such information in the absence of available data [1]. Here, we explore a … Continue reading “Identifying bias when sensitive attribute data is unavailable: Exploring Data from the HMDA”