Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships...

This course aims to teach learners about the history and evolution of artificial intelligence, deep learning, and its applications in speech recognition. By the end of the course, students will...

This course aims to teach learners about the application of deep learning in medical diagnoses. The learning outcomes include understanding traditional clinical diagnostic procedures,...

This course teaches how to create interfaces with rich physical properties through digital fabrication. The learning outcomes include understanding the importance of materials and shape,...

Both AI and cognitive science can gain by studying the human solutions to difficult computational problems [1]. My talk will focus on two problems: concept learning and question asking. Compared...

We will discuss the history and musical details of each work and give suggestions for pianists who are practicing and performing the compositions. We will also encounter related compositions by...

Biologically speaking, individuals emerge when the interests of potentially distinct entities are tied together, such that they evolve as a collective. From this perspective, we can make sense of...

This course explores the concept of whether the brain can perform back-propagation. The learning outcomes include understanding online stochastic gradient descent, reasons why the brain may not...

Virtual assistants, providing a voice interface to web services and IoTs, can potentially develop into monopolistic platforms that threaten consumer privacy and open competition. This talk...

This course aims to teach learners about bugs in cryptographic implementations. By the end of the course, students will be able to identify implementation mistakes in encryption methods,...

This course provides an architect's perspective on emerging technologies, focusing on topics such as Moore's Law, new devices, memories, 3D integration, and carbon nanotubes. Students will...

Stanford's CS330 course provides an overview of Multi-Task and Meta-Learning, exploring basics such as optimization-based meta-learning, nonparametric meta-learners, and Bayesian meta-learning....

Stanford CS234: Reinforcement Learning is a course designed for students interested in learning about the latest advancements in artificial intelligence. The course covers foundational topics...

This course provides an introduction to the field of machine learning, covering basic models such as linear regression and logistic regression, as well as more advanced techniques such as...

This course aims to teach students about software-centric visible light communication for the Internet of Things. The learning outcomes include understanding communication protocols,...

In conventional software development, the boundary between user experience (UX) design and engineering is well defined: designers create specifications based on end-user needs, then engineers...

The success of the abstract model of classical computation in terms of bits, logical operations, algorithms, and programming language constructs makes it easy to forget that computation is a...

This course covers the learning outcomes and goals of understanding dynamic code optimization and the NVIDIA Denver Processor. Students will learn about the TEGRA K1 with Dual Denver CPUs,...

This course aims to teach learners how to apply deep learning techniques to symbolic mathematics problems. The learning outcomes include understanding how to convert mathematical expressions...