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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
Future Blog Post
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Blog Post number 4
Published:
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Blog Post number 3
Published:
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Blog Post number 2
Published:
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Blog Post number 1
Published:
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portfolio
Portfolio item number 1
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talks
teaching
Efficient Algorithms and Intractable Problems (CS 170)
Undergraduate course, UC Berkeley, EECS, 1900
Teaches core algorithmic concepts in Computer Science, including Divide-and-Conquer, Graph, Greedy Algorithms, Dynamic Programming, Linear Programming, Reductions, P vs. NP, Streaming, etc.
Introduction to Artificial Intelligence (CS 188)
Undergraduate course, UC Berkeley, EECS, 1900
Overviews developments in AI, from searching algorithms to state-of-the-art RL and neural networks.
Neural Networks (CS 342)
Undergraduate course, UT Austin, CS, 1900
This course covers the basic building blocks and intuitions behind designing, training, tuning, and monitoring of deep networks. It covers both the theory of deep learning, as well as hands-on implementation sessions in pytorch. It also covers a series of application areas of deep networks in: computer vision, sequence modeling in natural language processing, deep reinforcement learning, generative modeling, and adversarial learning.
Artificial Intelligence (CS 343)
Undergraduate course, UT Austin, CS, 1900
This course provides a broad introduction to artificial intelligence. Topics include: problem solving, including search and game playing; knowledge and reasoning, including inference planning; reasoning under uncertainty; machine learning