Best OReilly Data Podcasts (2025)

1
Machine Learning for Operational Analytics and Business Intelligence 51:41

Play Pause

6y ago51:41

51:41

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 Lab.…

1
Machine learning for operational analytics and business intelligence 51:38

6y ago51:38

51:38

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 Lab. We had a…

1
Machine learning and analytics for time series data 40:31

6y ago40:31

40:31

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, an…

1
Machine Learning and Analytics for Time Series Data 40:33

6y ago40:33

40:33

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, an…

1
Understanding deep neural networks 39:31

6y ago39:31

39:31

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 a…

1
Understanding Deep Neural Networks 39:34

6y ago39:34

39:34

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 a…

1
Becoming a machine learning practitioner 33:22

6+ y ago33:22

33:22

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 some well-regarde…

1
Becoming a Machine Learning Practitioner 33:24

6+ y ago33:24

33:24

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 some well-regarde…

1
Labeling, transforming, and structuring training data sets for machine learning 40:51

6+ y ago40:51

40:51

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. Base…

1
Labeling, Transforming, and Structuring Training Data Sets for Machine Learning 40:54

6+ y ago40:54

40:54

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. Base…

1
Make data science more useful 35:04

6+ y ago35:04

35:04

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 develo…

1
Taming Chaos: Preparing for Your Next Incident 29:45

6+ y ago29:45

29:45

In this interview, Tim Craig and fellow Googler Gustavo Franco, a site reliability engineer (SRE), discuss the wide range of events that qualify as “incidents;” the need for a conscious, robust, and well-defined process for understanding them; the role of training; and how to get buy-in from management so you can spread incident response training t…

1
Make Data Science More Useful 35:06

6+ y ago35:06

35:06

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 develo…

1
Acquiring and sharing high-quality data 39:20

6+ y ago39:20

39:20

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 after Chen and…

1
Acquiring and Sharing High-Quality Data 39:23

6+ y ago39:23

39:23

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 after Chen and…

1
Tools for machine learning development 39:24

6+ y ago39:24

39:24

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:…

1
Tools for Machine Learning Development 39:27

6+ y ago39:27

39:27

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).…

1
Enabling end-to-end machine learning pipelines in real-world applications 42:53

6+ y ago42:53

42:53

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 within IBM focused on building open s…

1
Enabling End-to-End Machine Learning Pipelines in Real-World Applications 42:56

6+ y ago42:56

42:56

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 within IBM focused on building open s…

1
How to Get Started With Site Reliability Engineering (SRE) 38:32

6+ y ago38:32

38:32

At Google’s 2019 Cloud Next conference, I sat down with Stephen Thorne, site reliability engineer on Google’s customer reliability engineering team and co-author of "The Site Reliability Workbook," to talk about how organizations, both large and small, can use SRE to reduce operational costs, improve reliability, and create productive cross-functio…

1
Bringing scalable real-time analytics to the enterprise 37:12

6+ y ago37:12

37:12

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 executive…

1
Bringing Scalable Real-time Analytics to the Enterprise 37:14

6+ y ago37:14

37:14

In this episode of the Data Show, I spoke with Dhruba Borthakur (co-founder and CTO) and Shruti Bhat (SVP of Marketing) 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 executi…

1
Applications of data science and machine learning in financial services 42:32

6+ y ago42:32

42:32

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 conversation spannin…

1
Applications of Data Science and Machine Learning in Financial Services 42:35

6+ y ago42:35

42:35

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 conversation spanning…

1
Real-time entity resolution made accessible 27:09

6+ y ago27:09

27:09

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…

1
Real-Time Entity Resolution Made Accessible 27:11

6+ y ago27:11

27:11

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…

OReilly Data Podcasts

1
O'Reilly Data Show Podcast

O'Reilly Media

1
O'Reilly Radar Podcast - O'Reilly Media Podcast

O'Reilly Media

1
O'Reilly Security Podcast - O'Reilly Media Podcast

O'Reilly Media

1
O'Reilly Radar Podcast

O'Reilly Radar

1
O'Reilly Radar

O'Reilly Radar

1
Machine Learning for Operational Analytics and Business Intelligence 51:41

1
Machine learning for operational analytics and business intelligence 51:38

1
Machine learning and analytics for time series data 40:31

1
Machine Learning and Analytics for Time Series Data 40:33

1
Understanding deep neural networks 39:31

1
Understanding Deep Neural Networks 39:34

1
Becoming a machine learning practitioner 33:22

1
Becoming a Machine Learning Practitioner 33:24

1
Labeling, transforming, and structuring training data sets for machine learning 40:51

1
Labeling, Transforming, and Structuring Training Data Sets for Machine Learning 40:54

1
Make data science more useful 35:04

1
Taming Chaos: Preparing for Your Next Incident 29:45

1
Make Data Science More Useful 35:06

1
Acquiring and sharing high-quality data 39:20

1
Acquiring and Sharing High-Quality Data 39:23

1
Tools for machine learning development 39:24

1
Tools for Machine Learning Development 39:27

1
Enabling end-to-end machine learning pipelines in real-world applications 42:53

1
Enabling End-to-End Machine Learning Pipelines in Real-World Applications 42:56

1
How to Get Started With Site Reliability Engineering (SRE) 38:32

1
Bringing scalable real-time analytics to the enterprise 37:12

1
Bringing Scalable Real-time Analytics to the Enterprise 37:14

1
Applications of data science and machine learning in financial services 42:32

1
Applications of Data Science and Machine Learning in Financial Services 42:35

1
Real-time entity resolution made accessible 27:09

1
Real-Time Entity Resolution Made Accessible 27:11