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How Uber Uses Machine Learning To Improve Its Customer Service - The Click Reader

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Millions of tickets arrive at Uber's customer service department every week from its riders, drivers, eaters, etc. It is important for Uber to handle these tickets in a quick and efficient manner to retain its customers and fuel the companies growth. For this purpose, Uber has designed COTA or'Customer Obsession Ticket Assistant'. COTA is a Machine Learning and NLP powered tool that enables quick and efficient issue resolution of more than 90 per cent of Uber's inbound support tickets. For detailed information about different processes in the pipeline, please refer to this article by Uber. Uber is known to organize its processes using Machine Learning to achieve high speed and accuracy.


Artificial Intelligence: What Is Reinforcement Learning?

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Reinforcement learning is one of the most discussed, followed and contemplated topics in artificial intelligence (AI) as it has the potential to transform most businesses. In this article, I want to provide a simple guide that explains reinforcement learning and give you some practical examples of how it is used today. At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward. Similar to toddlers learning how to walk who adjust actions based on the outcomes they experience such as taking a smaller step if the previous broad step made them fall, machines and software agents use reinforcement learning algorithms to determine the ideal behavior based upon feedback from the environment. Depending on the complexity of the problem, reinforcement learning algorithms can keep adapting to the environment over time if necessary in order to maximize the reward in the long-term.


Uber wants to get better at predicting customer demand

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Uber wants to use machine learning to predict when a surge of people will be out looking for rides. The intention is to get more cabs on the road before surge pricing would normally kick in. That way, drivers will be ready and waiting for riders when the surge happens -- and riders won't be stuck waiting around. Here's how Jeff Schneider, the engineering leader of Uber's Advanced Technology Center, put it during a recent data technology conference: "This idea is if you can predict that demand, you get that information out there -- and you get that supply there ready for the demand so the surge pricing never even has to happen," he said, according to NPR. Uber already does this to some extent, but Schneider says that Uber wants "to find those Tuesday nights when it's not even raining and for some reason there's demand."


Uber starts teaching basic sign language in the app

Mashable

Uber is offering basic sign language lessons in its app, in an effort to support its deaf and hard of hearing drivers. Riders in North America will be able to see a card in the Uber app's messages section, offering to teach basic greetings such as "hello" and "thank you" in American Sign Language (ASL). SEE ALSO: 'See' sounds around you with these eyeglasses for the hard of hearing It'll also teach you how to sign your name in a sequence of videos, which is a pretty nifty addition. Uber, who has "thousands" of deaf drivers in the U.S. alone, says the new feature is in support of National Deaf Awareness Month, and it's certainly a step in the right direction. The company started including modifications to its UI for hard of hearing drivers back in 2015.


Human-Centered Design for Machine Learning IoT For All

@machinelearnbot

Machine learning (ML) is the science of helping computers discover patterns and relationships in data instead of being manually programmed. It's a powerful tool for creating personalized and dynamic experiences, and it's already driving everything from Netflix recommendations to autonomous cars.