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39:06

Deep Learning Applications in Business

Posted by Diego Klabjan  on  May 07, 2017 Posted by Diego Klabjan  on  May 07, 2017

Diego Klabjan discusses models, implementations, and challenges developing applications for trading, forecasting, and healthcare, detailing relevant models and issues adopting and deploying them.

21:07

Machine Learning at Scale

Posted by Aditya Kalro  on  Apr 18, 2017 Posted by Aditya Kalro  on  Apr 18, 2017

Aditya Kalro discusses using large-scale data for Machine Learning (ML) research and some of the tools Facebook uses to manage the entire process of training, testing, and deploying ML models.

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.

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.

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.

45:11

Policing the Stock Market with Machine Learning

Posted by Cliff Click  on  Mar 28, 2017 Posted by Cliff Click  on  Mar 28, 2017

Cliff Click talks about SCORE, a solution for doing Trade Surveillance using H2O, Machine Learning, and a whole lot of domain expertise and data munging.

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 2 Posted by Rob Harrop  on  Feb 02, 2017 2

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.

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