Category: Podcast

Podcast: Play in new window | Download (Duration: 40:10 — 27.8MB)

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We recently sat down with Kuba and Pavel from H2O to discuss how you can easily lift your Spark notebooks to the next level by adding some H20 to it using their open source Sparkling Water project.

In this second part of the interview, we go deeper into the technical details of Sparking Water and how you can deploy and use it in your environment. We end the conversation with a look at the roadmap and anything else the future may bring.

Continue reading “Episode 127 – Sparkling Water with H2O.AI (part 2)”

Podcast: Play in new window | Download (Duration: 26:26 — 18.4MB)

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The second news episode for 2019 is almost entirely devoted to practical AI with some tutorial notebooks and finding a parking space. We end this show with dire warnings of the impending Big Data induced Apocalypse! Continue reading “Episode 126 – Roaring News”

Podcast: Play in new window | Download (Duration: 51:21 — 35.5MB)

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We recently sat down with Kuba and Pavel from H2O to discuss how you can easily lift your Spark notebooks to the next level by adding some H20 to it using their open source Sparkling Water project.

In this first part of the interview, we cover the conceptual principles behind Sparkling water and discuss some existing use case implementations.

Continue reading “Episode 125 – Sparkling Water with H2O.AI (Part 1)”

Podcast: Play in new window | Download (Duration: 38:12 — 26.5MB)

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The Hortonworks -Cloudera merger has been finalized and the new CDP (Cloudera Data Platform) has been announced. We also talk about data mining bias, the good and bad of Hackathons and end on a rant about data sizes. Continue reading “Episode 124 – Roaring News”

Podcast: Play in new window | Download (Duration: 57:24 — 39.7MB)

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In episode 121 we discussed the first part of this story and now we conclude with a discussion of the data life-cycle considerations that apply to a Big Data and Advanced Analytics environment.

Continue reading “Episode 123 – Infrastructure and Data Lifecycle (part 2)”