Day: October 1, 2018

AI Reinforcement Learning

Overcoming Sparse Rewards in Reinforcement Learning

This video, a follow up from his intro video on reinforcement learning, Arxiv dives into three advanced papers that address the problem of the sparse reward setting in Deep Reinforcement Learning and pose interesting research directions for mastering unsupervised learning in autonomous agents.

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Machine Learning Reinforcement Learning

Mathematics of Dopamine

In this video, Siraj Raval explores how key reinforcement learning algorithms help explain how the human brain works, specifically through the lens of the neurotransmitter known as ‘dopamine’. These algorithms have been used to help train everything from autopilot systems for airplanes, to video game bots. TD-Learning, Rescorla-Wagner, Kalman Filters, and Bayesian Learning, all in one […]

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AI Reinforcement Learning

Comparing Humans with the Best Reinforcement Learning Algorithms

By leveraging powerful prior knowledge about how the world works, humans can quickly figure out efficient strategies in new and unseen environments. Currently, even state-of-the-art Reinforcement Learning algorithms typically don’t have strong priors and this is one of the fundamental challenges in current research on Transfer Learning. Related Links Paper referenced in the video Games

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Azure IoT

Routing Messages in Azure IoT Hub based on Device Twin

Check out this great demo of the new way to configure message routing in Azure IoT Hub using Device Twin properties and the updated UI in the Azure portal. Paul Montgomery, Senior Software Engineer in the Azure IoT Team shows us how this all works using an ESP32 based microcontroller, a temperature sensor, a glass […]

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Azure

A Conversation with Azure CTO, Mark Russinovich

Live Q&A with the Mark Russinovich, CTO of Azure, at Microsoft Ignite 2018.

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