In this episode of the Data Show, I speak with Peter Bailis, founder and CEO of Sisu, a startup that is using machine learning to improve operational analytics. Bailis is also an assistant professor of computer science at Stanford University, where he conducts research into data-intensive systems and where he is co-founder of the DAWN […]
In this episode of the Data Show, I speak with Arun Kejariwal of Facebook and Ira Cohen of Anodot (full disclosure: I’m an advisor to Anodot). This conversation stemmed from a recent online panel discussion we did, where we discussed time series data, and, specifically, anomaly detection and forecasting. Both Kejariwal (at Machine Zone, Twitter, […]
In this episode of the Data Show, I speak with Michael Mahoney, a member of RISELab, the International Computer Science Institute, and the Department of Statistics at UC Berkeley. A physicist by training, Mahoney has been at the forefront of many important problems in large-scale data analysis. On the theoretical side, his works spans algorithmic […]
In this episode of the Data Show, I speak with Kesha Williams, technical instructor at A Cloud Guru, a training company focused on cloud computing. As a full stack web developer, Williams became intrigued by machine learning and started teaching herself the ML tools on Amazon Web Services. Fast forward to today, Williams has built […]
In this episode of the Data Show, I speak with Alex Ratner, project lead for Stanford’s Snorkel open source project; Ratner also recently garnered a faculty position at the University of Washington and is currently working on a company supporting and extending the Snorkel project. Snorkel is a framework for building and managing training data. […]
In this episode of the Data Show, I speak with Cassie Kozyrkov, technical director and chief decision scientist at Google Cloud. She describes “decision intelligence” as an interdisciplinary field concerned with all aspects of decision-making, and which combines data science with the behavioral sciences. Most recently she has been focused on developing best practices that […]
In this episode of the Data Show, I spoke with Roger Chen, co-founder and CEO of Computable Labs, a startup focused on building tools for the creation of data networks and data exchanges. Chen has also served as co-chair of O’Reilly’s Artificial Intelligence Conference since its inception in 2016. This conversation took place the day […]
In this week’s episode of the Data Show, we’re featuring an interview Data Show host Ben Lorica participated in for the Software Engineering Daily Podcast, where he was interviewed by Jeff Meyerson. Their conversation mainly centered around data engineering, data architecture and infrastructure, and machine learning (ML). Here are a few highlights: Tools for productive […]
In this episode of the Data Show, I spoke with Nick Pentreath, principal engineer at IBM. Pentreath was an early and avid user of Apache Spark, and he subsequently became a Spark committer and PMC member. Most recently his focus has been on machine learning, particularly deep learning, and he is part of a group […]
In this episode of the Data Show, I spoke with Dhruba Borthakur (co-founder and CTO) and Shruti Bhat (SVP of Product) of Rockset, a startup focused on building solutions for interactive data science and live applications. Borthakur was the founding engineer of HDFS and creator of RocksDB, while Bhat is an experienced product and marketing […]
In this episode of the Data Show, I spoke with Jike Chong, chief data scientist at Acorns, a startup focused on building tools for micro-investing. Chong has extensive experience using analytics and machine learning in financial services, and he has experience building data science teams in the U.S. and in China. We had a great […]
In this episode of the Data Show, I spoke with Jeff Jonas, CEO, founder and chief scientist of Senzing, a startup focused on making real-time entity resolution technologies broadly accessible. He was previously a fellow and chief scientist of context computing at IBM. Entity resolution (ER) refers to techniques and tools for identifying and linking […]
In this episode of the Data Show, I spoke with Neelesh Salian, software engineer at Stitch Fix, a company that combines machine learning and human expertise to personalize shopping. As companies integrate machine learning into their products and systems, there are important foundational technologies that come into play. This shouldn’t come as a shock, as […]
In this episode of the Data Show, I spoke with Avner Braverman, co-founder and CEO of Binaris, a startup that aims to bring serverless to web-scale and enterprise applications. This conversation took place shortly after the release of a seminal paper from UC Berkeley (“Cloud Programming Simplified: A Berkeley View on Serverless Computing”), and this […]
In this episode of the Data Show, I spoke with Forough Poursabzi-Sangdeh, a postdoctoral researcher at Microsoft Research New York City. Poursabzi works in the interdisciplinary area of interpretable and interactive machine learning. As models and algorithms become more widespread, many important considerations are becoming active research areas: fairness and bias, safety and reliability, security […]
