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As a doctoral student she worked as an intern at Google Brain, where she worked on robot learning algorithms from deep predictive models. She delivered a massive open online course on deep reinforcement learning. [5] [6] She was the first woman to win the C.V. & Daulat Ramamoorthy Distinguished Research Award. [7]
Various techniques exist to train policies to solve tasks with deep reinforcement learning algorithms, each having their own benefits. At the highest level, there is a distinction between model-based and model-free reinforcement learning, which refers to whether the algorithm attempts to learn a forward model of the environment dynamics.
The Word and the World, A Large Lecture Intro to Humanities Course: In this multi-year project to create learning communities in a large lecture classes, a course web site presented (a)rich resources supporting the online course texts to engage students; (b) on-line assignments that structured the learners’ reading activities; and (c) an on ...
Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised ...
His machine learning course CS229 at Stanford is the most popular course offered on campus with over 1,000 students enrolling some years. [ 24 ] [ 25 ] As of 2020, three of most popular courses on Coursera are Ng's: Machine Learning (#1), AI for Everyone (#5), Neural Networks and Deep Learning (#6).
Udacity is the outgrowth of free computer science classes offered in 2011 through Stanford University. [9] Thrun has stated he hopes half a million students will enroll, after an enrollment of 160,000 students in the predecessor course at Stanford, Introduction to Artificial Intelligence, [10] and 90,000 students had enrolled in the initial two classes as of March 2012.
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