A Few Useful Things to Know About Machine Learning
Associated Papers
Other Meetings in this Series
Welcome to the Intelligence Group!
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Welcome to the Intelligence group! This meeting, we'll be discerning everyone's research interests, whether passive or active. Following that, we'll start narrowing paper topics to fill the 5 unplanned meetings so everyone can begin getting a feel for the breadth of computation as a field of research.
Deep Learning
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Abstract: Deep learning allows for computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state- of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.
Contributing Authors
John Muchovej
Founder of AI@UCF. Researcher in cognitive science and machine learning. Focusing on intuitive physics and intuitive psychology.