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46:36

Products and Prototypes with Keras

Posted by Micha Gorelick  on  Apr 08, 2017 Posted by Micha Gorelick  on  Apr 08, 2017

Micha Gorelick shows how to build a working product with Keras, a high-level deep learning framework, discussing design decisions, and demonstrating how to train and deploy a model.

49:40

Causal Consistency for Large Neo4j Clusters

Posted by Jim Webber  on  Apr 07, 2017 Posted by Jim Webber  on  Apr 07, 2017

Jim Webber explores the new Causal clustering architecture for Neo4j, how it allows users to read writes straightforwardly, explaining why this is difficult to achieve in distributed systems.

48:32

Our Concurrent Past; Our Distributed Future

Posted by Joe Duffy  on  Apr 07, 2017 Posted by Joe Duffy  on  Apr 07, 2017

Joe Duffy talks about the concurrency's explosion onto the mainstream over the past 15 years and attempts to predict what lies ahead for distributed programming, from now til 15 years into the future.

40:00

Deep Learning at Scale

Posted by Scott Le Grand  on  Apr 05, 2017 Posted by Scott Le Grand  on  Apr 05, 2017

Scott Le Grand describes his work at NVidia, Amazon and Teza, including the DSSTNE distributed deep learning framework.

43:41

Building Robust Machine Learning Systems

Posted by Stephen Whitworth  on  Apr 05, 2017 Posted by Stephen Whitworth  on  Apr 05, 2017

Stephen Whitworth talks about his experience at Ravelin, and provides useful practices and tips to help ensure our machine learning systems are robust, well audited, avoid embarrassing predictions.

46:52

Taming Complexity with Object-Oriented UX

Posted by Sophia Voychehovski  on  Apr 04, 2017 Posted by Sophia Voychehovski  on  Apr 04, 2017

Sophia Voychehovski discusses all the factors that cause complexity, the three key ways one can wrangle it and object-oriented UX.

39:52

Putting the ‘V’ Back in MVP

Posted by Ralf Jeffery  on  Apr 02, 2017 Posted by Ralf Jeffery  on  Apr 02, 2017

Ralf Jeffery explains the different types of MVP execution, why stakeholders struggle to support MVPs and how to deal with this issue, and how successful teams practice MVP design and execution.

34:33

Reactive & Asynchronous - Adventures with APIs in Financial Trading

Posted by Michael Barker  on  Apr 02, 2017 Posted by Michael Barker  on  Apr 02, 2017

Michael Barker discusses several low-latency APIs used for financial trading, what makes them fast and how they compare to HTTP/REST/JSON/XML APIs.

50:48

Big Data Infrastructure @ LinkedIn

Posted by Shirshanka Das  on  Apr 02, 2017 Posted by Shirshanka Das  on  Apr 02, 2017

Shirshanka Das describes LinkedIn’s Big Data Infrastructure and its evolution through the years, including details on the motivation and architecture of Gobblin, Pinot and WhereHows.

35:13

Using NLP, Machine Learning & Deep Learning Algorithms to Extract Meaning from Text

Posted by David Talby  on  Apr 02, 2017 Posted by David Talby  on  Apr 02, 2017

David Talby walks through building a natural language annotations pipeline with domain-specific annotators, and using deep learning to automatically expand and update taxonomies.

18:46

What is Business Agility?

Posted by Steve Denning  on  Apr 01, 2017 Posted by Steve Denning  on  Apr 01, 2017

Steve Denning discusses the three laws that are key to sustaining business agility: the law of the customer, the law of the small team and the law of the network.

14:06

Agility - Not Enough? Too Much? Trying to Find Just Right

Posted by Tim Lister  on  Apr 01, 2017 Posted by Tim Lister  on  Apr 01, 2017

Tim Lister discusses which departments of an organization can have much benefit from Agile and which will benefit a little or have an increased risk if using Agile.

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