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Podcast Highlights: O’Reilly Data Show

Today’s feature podcast series comes from venerable O’Reilly Media that brings us compelling books (with different animals on the cover) on data science, programming, AI, machine learning, etc. The O’Reilly Data Show explores the opportunities and methodologies propelling data science, big data, and AI.

Podcast Highlights: Towards Data Science

Today’s feature podcast series comes from one my favorite data science blogs, Towards Data Science, which has consistently high-quality content to expand your knowledge of the field. Use the link to browse the 21 podcast series. Enjoy!

Data Science at Microsoft – Interviews with Practitioners

In this technical brief I wanted to pass along some great resources in support how data scientists approach their profession and illustrate the kind of background a typical data scientist might have to become successful. insideBIGDATA previously featured four compelling podcast interviews with Microsoft data scientists.

Interview: Matt Winkler, Group Program Manager for Machine Learning at Microsoft

In this podcast interview, we caught up with Matt Winkler, Group Program Manager for Machine Learning at Microsoft, to get his take on the upward trajectory of data science, machine learning and the cloud – specifically Azure. Matt leads a team crafting tools and services to enable data scientists and developers to do more with their data. Originally from St. Louis, Matt has been at Microsoft for 11 years working on developer tools and cloud services such as the .NET Framework, Visual Studio, Azure Websites, Data Lake and HDInsight.

Interview: Jennifer Marsman, Principal Software Development Engineer at Microsoft

In this podcast interview, I caught up with Jennifer Marsman, Principal Software Development Engineer at Microsoft, to find out what it’s like to be a data scientist at Microsoft and get her take on the upward trajectory of AI and deep learning that we’re seeing in the industry today.

Interview: Dr. Danielle Dean, Senior Data Scientist Lead at Microsoft

In this podcast interview, I caught up with Dr. Danielle Dean, Senior Data Scientist Lead at Microsoft in the Algorithms and Data Science Group within the Cloud and Enterprise Division, to find out about her experience at Microsoft and get her take on the upward trajectory of AI and deep learning that we’re seeing in the industry today.

Interview: Anusua Trivedi, Data Scientist on Microsoft’s Advanced Data Science & Strategic Initiatives Team

In this podcast interview, I caught up with Anusua Trivedi, a Data Scientist on Microsoft’s ADS team, to get her take on the upward trajectory of AI and deep learning that we’re seeing in the industry today.

Slidecast: Announcing the Nvidia Deep Learning SDK

In this slidecast, Marc Hamilton from Nvidia describes the latest updates to the company’s Deep Learning Platform. “Great hardware needs great software. To help data scientists and developers make the most of the vast opportunities in deep learning, we’re announcing today at the International Supercomputing show, ISC16, a trio of new capabilities for our deep learning software platform. The three — NVIDIA DIGITS 4, CUDA Deep Neural Network Library (cuDNN) 5.1 and the new GPU Inference Engine (GIE) — are powerful tools that make it even easier to create solutions on our platform.”

The Hadooponomics Podcast Series

The Hadooponomics Podcast series is a creation of Blue Hill Research and hosted by James Haight, a principal analyst at the company. The mission of the Hadooponomics Podcast series is simple: to advance the Big Data conversation beyond its traditional buzz-heavy roots, and to take a look at the real story of what drives the value of Big Data.

Podcast: New Xeons Power Cisco UCS Realtime Analytics

Jim McHugh from Cisco describes how the new Intel Xeon processor E7 v3 processor family will bring to Cisco UCS systems in the big data and analytics arena. He emphasizes how new insights driven by big-data can help businesses become intelligence-driven to create a perpetual and renewable competitive edge within their field.