The O'Reilly Media Podcast spreads the knowledge of innovators. At O’Reilly, a big part of our business is paying attention to what’s new and interesting in the world of technology. The O'Reilly Media Podcast features interviews with the people working on the forefront of technology.

O'Reilly Media Podcast

it is playlist about data science. I'm putting here all podcast in english in related topic. If you know something that should be here please drop me a message with link. And follow me on twitter: @hyzhak_en

data science

Data Lake

O’Reilly’s Mac Slocum talks with Edd Dumbbell, VP of strategy at Silicon Valley Data Science, about the data lake, the opportunities the model presents, and the driving forces behind the concept. In the second segment, O’Reilly’s big data guru Ben Lorica chats with Rajiv Maheswaran, CEO of SecondSpectrum, about spatial-temporal pattern recognition — what Maheswaran calls “the science of moving dots.”

The data lake model is a powerhouse for invention

What does it take to build a data-driven culture? In this O’Reilly Podcast episode, I pose that question to Ashish Thusoo, founder of Qubole. With his co-founder Joydeep Sen Sarma, Thusoo built a self-service data infrastructure at Facebook beginning in 2007. That infrastructure transformed Facebook’s culture and became part of practically every product decision that the company made.

Building a Data-Driven Culture

In this episode I spoke with Michael Franklin, co-director of UC Berkeley’s AMPLab and chair of the Department of Computer Science at the University of Chicago. AMPLab is well-known in the data community for having originated Apache Spark, Alluxio (formerly Tachyon) and many other open source tools. Today marks the start of a two-day symposium commemorating the end of AMPLab, and we took the opportunity to reflect on its impressive accomplishments.

Building the Next-Generation Big Data Analytics Stack

In this episode of the Super Data Science Podcast, I chat with Chief Data Scientist Damian R Mingle. You will learn about how to build models with 95% accuracy rates, know the 3 top tips on quick wins and winning people over; and get ideas on how to save lives with data science.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/13

The Super Data Science Podcast: Big Data | Analytics Careers | Mentors | Success

SDS 013 : 95% Accuracy Models, Winning People Over, and Saving Lives with Damian Mingle

In this episode, I sit down with Brad Knox, founder and CEO of Emoters, a startup building a product called bots_alive—animal-like robots that have a strong illusion of life. We chat about the approach the company is taking, why robots or agents that pass themselves off as human without any transparency should be illegal, and some challenges and applications of reinforcement learning and interactive machine learning.

Brad Knox on Creating a Strong Illusion of Life

In this episode I spoke with Ion Stoica, cofounder and chairman of Databricks. Stoica is also a professor of computer science at UC Berkeley, where he serves as director of the new RISE Lab (the successor to AMPLab). Fresh off the incredible success of AMPLab, RISE seeks to build tools and platforms that enable sophisticated real-time applications on live data, while maintaining strong security. As Stoica points out, users will increasingly expect security guarantees on systems that rely on online machine learning algorithms that make use of personal or proprietary data.

Data is Only as Valuable as the Decisions it Enables

Building a Data Lake in AWS - Mick Bass and Carla Cole - 47Lining

In this podcast episode, O’Reilly’s Shannon Cutt talks with Damon Feldman, solutions director at MarkLogic, a company that has developed an operational and transactional NoSQL database that integrates data silos to give customers a single view of their data. They discuss data lakes, data hubs, integrating data in a lake format, data governance related to security, and more.

Damon Feldman on Combining a Data Hub and Data Lake

In this episode of the O’Reilly podcast, I speak with Han Yang, senior product manager at Cisco, working on analytics solutions. We discuss the impact of data analytics across industries, building data lifecycles for Internet of Things (IoT) applications, and advice for establishing successful analytics and machine learning projects.

Building Data Lifecycles for IoT Projects With Edge Analytics

In this podcast, Wayne Eckerson and James Serra discuss myths of modern data management. Some of the myths discussed include 'all you need is a data lake', 'the data warehouse is dead', 'we don’t need OLAP cubes anymore', 'cloud is too expensive and latency is too slow', 'you should always use a NoSQL product over a RDBMS.'

Serra is big data and data warehousing solutions architect at Microsoft with over thirty years of IT experience. He is a popular blogger and speaker and has presented at dozens of Microsoft PASS and other events. Prior to Microsoft, Serra was an independent data warehousing and business intelligence architect and developer.

James Serra: Myths of Modern Data Management

In a recent episode of the O’Reilly Media Podcast, we spoke with George Miranda about the importance of service mesh technology in creating reliable distributed systems. As discussed in the new report The Service Mesh: Resilient Service-to-Service Communication for Cloud Applications, service mesh technology has emerged as a popular tool for companies looking to build cloud-native applications that are reliable and secure.

During the podcast, we discussed the problems a service mesh infrastructure solves and the service mesh features you’ll find most valuable. We also talked about how to choose the right service mesh for your organization, the challenges involved in getting it deployed to production, and the best ways for getting started with a service mesh.

How to Choose and Deploy a Service Mesh

In this episode of the O’Reilly Media Podcast, Rachel Roumeliotis, VP of content strategy at O’Reilly, sat down with Daniel Krook, IBM developer advocate. They discussed how developers across industries can participate in the Call for Code initiative, the benefits of the program, support from its charitable partners—United Nations Human Rights and the American Red Cross—and the positive impacts IBM hopes to achieve by investing in Call for Code.

Developers Worldwide Will Collaborate on Solutions to Save Lives in Call For Code

This episode of the O’Reilly Podcast, features a conversation on serverless and Kubernetes, with Kelsey Hightower, developer advocate for Google Cloud Platform at Google (and co-author of "Kubernetes: Up and Running"), and Chris Gaun, Kubernetes product marketing manager at Mesosphere.

Kelsey Hightower and Chris Gaun on Serverless and Kubernetes

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-functional teams.

How to Get Started With Site Reliability Engineering (SRE)

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 throughout an organization.

Taming Chaos: Preparing for Your Next Incident

O'Reilly Media spreads the knowledge of innovators. At O’Reilly, a big part of our business is paying attention to what’s new and interesting in the world of technology. We have a pretty good record at having anticipated some of the big technology developments in recent history. For instance, we launched the first commercial Web site, GNN, in 1993; we organized the meeting at which the term “open source” was first adopted; we were early investors in Blogger, which helped launch the blogging revolution; and more recently, our Web 2.0 conference launched a world-wide meme. We call this predictive sense the “O’Reilly Radar.” And while we’re certainly not always right, we are, at least, good at making interesting guesses.

Our methodology is simple: we draw from the wisdom of the alpha geeks in our midst, paying attention to what’s interesting to them, amplifying these weak signals, and seeing where they fit into the innovation ecology. Add to that the original research conducted by our Research team, and you start to get a good picture of what the technology world is thinking about.

Damon Feldman on Combining a Data Hub and Data Lake

O'Reilly Radar