Podcasts by OReilly Data Show Podcast
The O'Reilly Data Show Podcast explores the opportunities and techniques driving big data, data science, and AI.
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Machine learning for operational analytics and business intelligence from 2019-10-10T16:00:10
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 professo...
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Machine learning and analytics for time series data from 2019-09-26T16:00:06
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 d...
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Understanding deep neural networks from 2019-09-12T16:00:52
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 tr...
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Becoming a machine learning practitioner from 2019-08-29T16:00:26
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 in...
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Labeling, transforming, and structuring training data sets for machine learning from 2019-08-15T16:00:20
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...
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Make data science more useful from 2019-08-01T16:00:15
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 interdiscipl...
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Acquiring and sharing high-quality data from 2019-07-18T16:00:12
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 ...
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Tools for machine learning development from 2019-07-03T16:00:51
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 J...
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Enabling end-to-end machine learning pipelines in real-world applications from 2019-06-20T16:10:07
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 ...
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Bringing scalable real-time analytics to the enterprise from 2019-06-09T16:00
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 scienc...
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Applications of data science and machine learning in financial services from 2019-05-23T16:00
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 an...
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Real-time entity resolution made accessible from 2019-05-09T14:00
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 w...
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Why companies are in need of data lineage solutions from 2019-04-25T15:15
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 in...
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What data scientists and data engineers can do with current generation serverless technologies from 2019-04-11T15:30
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 to...
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It’s time for data scientists to collaborate with researchers in other disciplines from 2019-03-28T16:45
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 interpretab...
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Algorithms are shaping our lives—here’s how we wrest back control from 2019-03-14T16:10
In this episode of the Data Show, I spoke with Kartik Hosanagar, professor of technology and digital business, and professor of marketing at The Wharton School of the University of Pennsylvania. &n...
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Why your attention is like a piece of contested territory from 2019-02-28T17:00
In this episode of the Data Show, I spoke with P.W. Singer, strategist and senior fellow at the New America Foundation, and a contributing editor at Popular Science. He is co-author of an excellent...
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The technical, societal, and cultural challenges that come with the rise of fake media from 2019-02-14T19:05
In this episode of the Data Show, I spoke with Siwei Lyu, associate professor of computer science at the University at Albany, State University of New York. Lyu is a leading expert in digital media...
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Using machine learning and analytics to attract and retain employees from 2019-01-31T19:00
In this episode of the Data Show, I spoke with Maryam Jahanshahi, research scientist at TapRecruit, a startup that uses machine learning and analytics to help companies recruit more effectively. In...
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How machine learning impacts information security from 2019-01-17T18:50
In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer and legal engineer at Immuta, a company building data management tools tuned for data science. Burt and cybersecuri...
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In the age of AI, fundamental value resides in data from 2019-01-03T16:30
In this episode of the Data Show, I spoke with Haoyuan Li, CEO and founder of Alluxio, a startup commercializing the open source project with the same name (full disclosure: I’m an advisor to Allux...
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Trends in data, machine learning, and AI from 2018-12-20T18:00
For the end-of-year holiday episode of the Data Show, I turned the tables on Data Show host Ben Lorica to talk about trends in big data, machine learning, and AI, and what to look for in 2019. Lori...
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Tools for generating deep neural networks with efficient network architectures from 2018-12-06T18:05
In this episode of the Data Show, I spoke with Alex Wong, associate professor at the University of Waterloo, and co-founder of DarwinAI, a startup that uses AI to address foundational challenges wi...
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Building tools for enterprise data science from 2018-11-21T19:00
In this episode of the Data Show, I spoke with Vitaly Gordon, VP of data science and engineering at Salesforce. As the use of machine learning becomes more widespread, we need tools that will allow...
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Lessons learned while helping enterprises adopt machine learning from 2018-11-08T17:20
In this episode of the Data Show, I spoke with Francesca Lazzeri, an AI and machine learning scientist at Microsoft, and her colleague Jaya Mathew, a senior data scientist at Microsoft. We conducte...
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Machine learning on encrypted data from 2018-10-25T15:15
In this episode of the Data Show, I spoke with Alon Kaufman, CEO and co-founder of Duality Technologies, a startup building tools that will allow companies to apply analytics and machine learning t...
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How social science research can inform the design of AI systems from 2018-10-11T15:35
In this episode of the Data Show, I spoke with Jacob Ward, a Berggruen Fellow at Stanford University. Ward has an extensive background in journalism, mainly covering topics in science and technolog...
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Why it’s hard to design fair machine learning models from 2018-09-27T15:50
In this episode of the Data Show, I spoke with Sharad Goel, assistant professor at Stanford, and his student Sam Corbett-Davies. They recently wrote a survey paper, “A Critical Review of Fair Machi...
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Using machine learning to improve dialog flow in conversational applications from 2018-09-13T15:35
In this episode of the Data Show, I spoke with Alan Nichol, co-founder and CTO of Rasa, a startup that builds open source tools to help developers and product teams build conversational application...
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Building accessible tools for large-scale computation and machine learning from 2018-08-30T14:00
In this episode of the Data Show, I spoke with Eric Jonas, a postdoc in the new Berkeley Center for Computational Imaging. Jonas is also affiliated with UC Berkeley’s RISE Lab. It was at a RISE Lab...
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Simplifying machine learning lifecycle management from 2018-08-16T15:25
In this episode of the Data Show, I spoke with Harish Doddi, co-founder and CEO of Datatron, a startup focused on helping companies deploy and manage machine learning models. As companies move from...
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How privacy-preserving techniques can lead to more robust machine learning models from 2018-08-02T15:00
In this episode of the Data Show, I spoke with Chang Liu, applied research scientist at Georgian Partners. In a previous post, I highlighted early tools for privacy-preserving analytics, both for i...
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Specialized hardware for deep learning will unleash innovation from 2018-07-19T15:05
In this episode of the Data Show, I spoke with Andrew Feldman, founder and CEO of Cerebras Systems, a startup in the blossoming area of specialized hardware for machine learning. Since the release ...
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Data regulations and privacy discussions are still in the early stages from 2018-07-05T17:05
In this episode of the Data Show, I spoke with Aurélie Pols of Mind Your Privacy, one of my go-to resources when it comes to data privacy and data ethics. This interview took place at Strata Data L...
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Managing risk in machine learning models from 2018-06-21T15:10
In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer at Immuta, and Steven Touw, co-founder and CTO of Immuta. Burt recently co-authored a white paper on managing risk ...
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The real value of data requires a holistic view of the end-to-end data pipeline from 2018-06-07T15:05
In this episode of the Data Show, I spoke with Ashok Srivastava, senior vice president and chief data officer at Intuit. He has a strong science and engineering background, combined with years of a...
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The evolution of data science, data engineering, and AI from 2018-05-24T18:10
This episode of the Data Show marks our 100th episode. This podcast stemmed out of video interviews conducted at O’Reilly’s 2014 Foo Camp. We had a collection of friends who were key members of the...
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Companies in China are moving quickly to embrace AI technologies from 2018-05-10T18:00
In this episode of the Data Show, I spoke with Jason Dai, CTO of Big Data Technologies at Intel, and one of my co-chairs for the AI Conference in Beijing. I wanted to check in on the status of BigD...
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Teaching and implementing data science and AI in the enterprise from 2018-04-26T15:25
In this episode of the Data Show, I spoke with Jerry Overton, senior principal and distinguished technologist at DXC Technology. I wanted the perspective of someone who works across industries and ...
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The importance of transparency and user control in machine learning from 2018-04-12T18:15
In this episode of the Data Show, I spoke with Guillaume Chaslot, an ex-YouTube engineer and founder of AlgoTransparency, an organization dedicated to helping the public understand the profound imp...
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What machine learning engineers need to know from 2018-03-29T15:20
In this episode of the Data Show, I spoke with Jesse Anderson, managing director of the Big Data Institute, and my colleague Paco Nathan, who recently became co-chair of Jupytercon. This conve...
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How to train and deploy deep learning at scale from 2018-03-15T17:30
In this episode of the Data Show, I spoke with Ameet Talwalkar, assistant professor of machine learning at CMU and co-founder of Determined AI. He was an early and key contributor to Spark MLlib an...
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Using machine learning to monitor and optimize chatbots from 2018-03-06T18:35
In this episode of the Data Show, I spoke with Ofer Ronen, GM of Chatbase, a startup housed within Google’s Area 120. With tools for building chatbots becoming accessible, conversational interfaces...
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Unleashing the potential of reinforcement learning from 2018-03-01T17:05
In this episode of the Data Show, I spoke with Danny Lange, VP of AI and machine learning at Unity Technologies. Lange previously led data and machine learning teams at Microsoft, Amazon, and Uber,...
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Graphs as the front end for machine learning from 2018-02-15T17:35
In this episode of the Data Show, I spoke with Leo Meyerovich, co-founder and CEO of Graphistry. Graphs have always been part of the big data revolution (think of the large graphs generated by the ...
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Machine learning needs machine teaching from 2018-02-01T17:10
In this episode of the Data Show, I spoke with Mark Hammond, founder and CEO of Bonsai, a startup at the forefront of developing AI systems in industrial settings. While many articles have been wri...
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How machine learning can be used to write more secure computer programs from 2018-01-18T18:00
In this episode of the Data Show, I spoke with Fabian Yamaguchi, chief scientist at ShiftLeft. His 2015 Ph.D. dissertation sketched out how the combination of static analysis, graph mining, and mac...
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Bringing AI into the enterprise from 2018-01-04T19:50
In this episode of the Data Show, I spoke with Kristian Hammond, chief scientist of Narrative Science and professor of EECS at Northwestern University. He has been at the forefront of helping compa...
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How machine learning will accelerate data management systems from 2017-12-21T18:35
In this episode of the Data Show, I spoke with Tim Kraska, associate professor of computer science at MIT. To take advantage of big data, we need scalable, fast, and efficient data management syste...
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Machine learning at Spotify: You are what you stream from 2017-12-07T17:30
In this episode of the Data Show, I spoke with Christine Hung, head of data solutions at Spotify. Prior to joining Spotify, she led data teams at the NY Times and at Apple (iTunes). Having led team...
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The current state of Apache Kafka from 2017-11-22T18:35
In this episode of the Data Show, I spoke with Neha Narkhede, co-founder and CTO of Confluent. As I noted in a recent post on “the age of machine learning,” data integration and data enrichment are...
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Building a natural language processing library for Apache Spark from 2017-11-09T20:40
When I first discovered and started using Apache Spark, a majority of the use cases I used it for involved unstructured text. The absence of libraries meant rolling my own NLP utilities, and, in ma...
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Machine intelligence for content distribution, logistics, smarter cities, and more from 2017-10-26T18:20
In this episode of the Data Show, I spoke with Rhea Liu, analyst at China Tech Insights, a new research firm that is part of Tencent’s Online Media Group. If there’s one place where AI and machine ...
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Vehicle-to-vehicle communication networks can help fuel smart cities from 2017-10-12T15:34
In this episode of the Data Show, I spoke with Bruno Fernandez-Ruiz, co-founder and CTO of Nexar. We first met when he was leading Yahoo! technical teams charged with delivering a variety of large-...
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Transforming organizations through analytics centers of excellence from 2017-09-28T17:45
In this episode of the Data Show, I spoke with Carme Artigas, co-founder and CEO of Synergic Partners (a Telefonica company). As more companies adopt big data technologies and techniques, it’s usef...
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The state of machine learning in Apache Spark from 2017-09-14T14:49
In this episode of the Data Show, we look back to a recent conversation I had at the Spark Summit in San Francisco with Ion Stoica (UC Berkeley professor and executive chairman of Databricks) and M...
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Effective mechanisms for searching the space of machine learning algorithms from 2017-08-31T20:05
In this episode of the Data Show, I spoke with Ken Stanley, founding member of Uber AI Labs and associate professor at the University of Central Florida. Stanley is an AI researcher and a leading p...
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How Ray makes continuous learning accessible and easy to scale from 2017-08-17T16:35
In this episode of the Data Show, I spoke with Robert Nishihara and Philipp Moritz, graduate students at UC Berkeley and members of RISE Lab. I wanted to get an update on Ray, an open source distri...
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Why AI and machine learning researchers are beginning to embrace PyTorch from 2017-08-03T17:25
In this episode of the Data Show, I spoke with Soumith Chintala, AI research engineer at Facebook. Among his many research projects, Chintala was part of the team behind DCGAN (Deep Convolutional G...
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How big data and AI will reshape the automotive industry from 2017-07-20T19:10
In this episode of the Data Show, I spoke with Evangelos Simoudis, co-founder of Synapse Partners and a frequent contributor to O’Reilly. He recently published a book entitled The Big Data Opportun...
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