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36:27

Haskell in the Newsroom

Posted by Erik Hinton  on  Apr 02, 2014

Erik Hinton discusses the successes and failures of making a cultural shift in the newsroom at NYT to accept Haskell and some of the projects Haskell has been used for.

39:12

An API for Distributed Computing

Posted by Cliff Click  on  Feb 22, 2014

Cliff Click introduces a coding style & API for in-memory analytics that handles datasets from 1K to 1TB without changing a line of code and clusters with TB of RAM and hundreds of CPUs.

44:45

From The Lab To The Factory: Building A Production Machine Learning Infrastructure

Posted by Josh Wills  on  Jan 16, 2014

Josh Wills discusses using Hadoop technologies to build real-time data analysis models with a focus on strategies for data integration, large-scale machine learning, and experimentation.

46:05

R for Big Data

Posted by Indrajit Roy  on  Dec 15, 2013

Indrajit Roy presents HP Labs’ attempts at scaling R to efficiently perform distributed machine learning and graph processing on industrial-scale data sets.

33:33

Deploying Machine Learning and Data Science at Scale

Posted by Nick Kolegraff  on  Dec 01, 2013

Nick Kolegraff discusses common problems and architecture to support all the phases of data science and how to start a data science initiative, sharing lessons from Accenture, Best Buy, and Rackspace.

43:47

Functional Programming for Optimization Problems with City of Palo Alto Open Data

Posted by Paco Nathan  on  Nov 23, 2013

Paco Nathan reviews an example data analysis application written in Cascalog used for a recommender system based on City of Palo Alto Open Data.

37:49

Add ALL the Things: Abstract Algebra Meets Analytics

Posted by Avi Bryant  on  Nov 20, 2013 4

Avi Bryant discusses how the laws of group theory provide a useful codification of the practical lessons of building efficient distributed and real-time aggregation systems.

41:19

"Big Data" Agile Analytics

Posted by Ken Collier  on  Oct 27, 2013

Ken Collier discusses Agile Analytics, a combination of sophisticated analytics techniques, lean learning principles, agile delivery methods, and "big data" technologies.

45:11

Making the Internet a Better Place: Scaling AppNexus

Posted by Mike Nolet  on  Oct 18, 2013

Mike Nolet shares lessons learned scaling AppNexus and architectural details of their system processing 30TB/day: Hadoop, load balancer-free DNS architecture built in GSLB and Keepalived, and real-time data streaming built in C.

36:45

Apache Drill - Interactive Query and Analysis at Scale

Posted by Michael Hausenblas  on  Oct 13, 2013

Michael Hausenblas introduces Apache Drill, a distributed system for interactive analysis of large-scale datasets, including its architecture and typical use cases.

43:06

A Little Graph Theory for the Busy Developer

Posted by Jim Webber  on  Oct 03, 2013

Jim Webber explores analytic techniques for graph data, discussing innate properties of (social) graphs from fields like anthropology and sociology. By understanding the forces and tensions within the graph structure and applying some graph theory, we'll be able to predict how the graph will evolve over time.

28:12

A Guide to Python Frameworks for Hadoop

Posted by Uri Laserson  on  Oct 03, 2013

Uri Laserson reviews the different available Python frameworks for Hadoop, including a comparison of performance, ease of use/installation, differences in implementation, and other features.

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