Highlight Sessions from Alibaba, Uber, The Washington Post – at Predictive Analytics World London

The Predictive Analytics World London 2018 (Sep 17-18) agenda is now live. Have a look at what all the excitement is about!
 
Predictive Analytics World for Business - Highlight Sessions from Alibaba, Uber, The Washington Post!

The 2018 Highlight Sessions have just been announced!

The Predictive Analytics World London 2018 agenda is now live. 
Have a look at what all the excitement is about!

 

In this talk, Vikram Godse will discuss Alibaba’s multi-factor dispatching and route planning model, which is used to optimize the real-time planning of their three million delivery riders delivering from 1.3 million partner shops. He will discuss static, dynamic and behavioral factors and constraints within this model, as well as how deployment is scaled in the Alibaba cloud, resulting in a response time of 500ms and cost savings of several hundred million dollars per year.

To scale comment moderation, the Washington Post developed ModBot. ModBot contains a set of predictive models trained on tens of thousands of comments with human moderated labels. The problem of comments moderation is considered as a classification task. Sam Han will explain how he and his team build the models, refine the models based on their moderation criteria, and then deploy ModBot in the production environment for more efficient and economical comments moderation.

Applied deep learning has fast become a standard tool for many industry machine learning applications. New advances in neural network techniques have opened the doors to solving problems at scale that were out of reach until recently. Because of these advances, applications such as in image recognition for self-driving cars, medical image classification, text translation, and fake news detection are both tractable and often the industry standard. In this keynote, Mike Tamir, who heads the

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