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48:32

Predictability in ML Applications

Posted by Claudia Perlich  on  Mar 23, 2017 Posted by Claudia Perlich  on  Mar 23, 2017

Claudia Perlich presents scenarios in which the combination of different and highly informative features can have significantly negative overall impact on the usefulness of predictive modeling.

38:49

Using Bayesian Optimization to Tune Machine Learning Models

Posted by Scott Clark  on  Feb 07, 2017 Posted by Scott Clark  on  Feb 07, 2017

Scott Clark introduces Bayesian Global Optimization as an efficient way to optimize ML model parameters, explaining the underlying techniques and comparing it to other standard methods.

34:07

Machine Learning Your Way to Smarter API Error Responses

Posted by Steven Cooper  on  Feb 05, 2017 Posted by Steven Cooper  on  Feb 05, 2017

Steven Cooper discusses using machine learning to understand malformed API requests to not only respond with a best fit response, but capture the user errors for future responses.

52:22

Autonomous Operations: Microservices, ML and AI

Posted by Rob Harrop  on  Feb 02, 2017 1 Posted by Rob Harrop  on  Feb 02, 2017 1

Rob Harrop discusses the increasing automated field of operations and what the future might hold when machine learning and AI techniques are brought to bear on the problem of systems operations.

50:13

Scaling Quality on Quora Using Machine Learning

Posted by Nikhil Garg  on  Jan 15, 2017 Posted by Nikhil Garg  on  Jan 15, 2017

Nikhil Garg talks about the various Machine Learning problems that are important for Quora to solve in order to keep the quality high at such a massive scale.

47:20

The Art of Relevance and Recommendations

Posted by Clarence Chio  on  Jan 15, 2017 Posted by Clarence Chio  on  Jan 15, 2017

Clarence Chio talks about the creation of a real-world relevance and recommendation system from scratch.

27:13

Operationalizing Data Science Using Cloud Foundry

Posted by Lawrence Spracklen  on  Jan 12, 2017 Posted by Lawrence Spracklen  on  Jan 12, 2017

Lawrence Spracklen creates a machine learning model leveraging data within MPP databases such as Apache HAWQ or Greenplum integrated with Chorus and then deploying this as a microservice on PCF.

31:03

TensorFlow: A Flexible, Scalable & Portable System

Posted by Rajat Monga  on  Dec 17, 2016 Posted by Rajat Monga  on  Dec 17, 2016

Rajat Monga talks about why Google built TensorFlow, an open source software library for numerical computation using data flow graphs, and what were some of the technical challenges in building it.

58:25

Impact of Machine Learning Systems in Industries

Posted by Teymur Sadikhov  on  Dec 11, 2016 Posted by Teymur Sadikhov Bhairav Mehta Hollin Wilkins Xinghua Lou Alok Agarwal  on  Dec 11, 2016

The panelists discuss the impact machine learning is having on various industries.

34:13

MLeap: Release Spark ML Models

Posted by Hollin Wilkins  on  Dec 04, 2016 Posted by Hollin Wilkins  on  Dec 04, 2016

Hollin Wilkins discusses the reasons behind MLeap, outes the programming time saved by using it, shows benchmarks of several online models, and provides a demo and examples of using it in practice.

32:43

Machine Learning Exposed!

Posted by James Weaver  on  Nov 25, 2016 1 Posted by James Weaver  on  Nov 25, 2016 1

James Weaver takes a deeper dive into machine learning topics such as supervised learning, unsupervised learning, and deep learning, surveying various machine learning APIs and platforms.

43:27

Overview of Artificial Intelligence and Its Use in Analyzing “Voice of Cancer Patients”

Posted by Alok Aggarwal  on  Nov 20, 2016 Posted by Alok Aggarwal  on  Nov 20, 2016

Alok Aggarwal overviews Artificial Intelligence and discusses a use case, “Voice of Cancer Patients” that uses ML and NLP algorithms to analyze unstructured text written by cancer patients.

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