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43:05

Design Patterns for Large-Scale Real-Time Learning

Posted by Sean Owen  on  Apr 15, 2014

Sean Owen provides examples of operational analytics projects in the field, presenting a reference architecture and algorithm design choices for a successful implementation based on his experience with customers and Oryx/Cloudera.

40:29

Creative Machines

Posted by Joseph Wilk  on  Feb 10, 2014

Joseph Wilk addresses the questions if machines can be creative and what's the place of artists in such a world?

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.

41:14

Machine Learning & Recommender Systems at Netflix Scale

Posted by Xavier Amatriain  on  Jan 16, 2014

Xavier Amatriain discusses the machine learning algorithms and architecture behind Netflix' recommender systems, offline experiments and online A/B testing.

38:46

Machine Learning for Relevance and Serendipity

Posted by Jenny Finkel  on  Oct 30, 2013

Jenny Finkel showcases Prismatic's use of machine learning and language processing to provide targeted content to their users based on a model built on users' way of interacting with their website.

Reverend Bayes, Meet Countess Lovelace: Machine Learning and Programming

Posted by Andy Gordon  on  Jan 22, 2013 1

Andy Gordon discusses machine learning using functional programming, explaining how Infer.NET Fun turns the succinct syntax of F# into an executable modeling language for Bayesian machine learning.

Machine Learning: A Love Story

Posted by Hilary Mason  on  Nov 09, 2010 16

Hilary Mason presents the history of machine learning covering some of the most significant developments taking place over the last two decades, especially the fundamental math and algorithmic tools employed. She also exemplifies how machine learning is used by bit.ly to discover various statistical information about users.

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