Computer Information Systems - Network Administration Program @ HFC

Graduate to a more difficult class of problems: learning from images and auditory information. Here, it makes sense to address the task more or less the way the brain does, using a form of computation called a neural network. Explore the general characteristics of this powerful tool. Among the examples, compare decision-tree and neural-network approaches to recognizing handwritten digits.

Continue your study of machine learning and language by seeing how computers not only read text, but how they can also generate it. Explore the current state of machine translation, which rivals the skill of human translators. Also, learn how algorithms handle a game that Professor Littman played with his family, where a given phrase is expanded piecemeal to create a story.

With the technological development of sensors, feedback control, Bluetooth, and machine learning, we can now network not just computers, but "things" as well. Discover the enormous advantages this "Internet of Things" can provide—from health care to transportation to manufacturing—if we can adequately address the significant concerns regarding privacy and security.

Discover how the ImageNet challenge helped revive the field of neural networks through a technique called deep learning, which is ideal for tasks such as computer vision. Consider the problem of image recognition and the steps deep learning takes to solve it. Dr. Littman throws out his own challenge: Train a computer to distinguish foot files from cheese graters.