Microsoft combined have invested billions of dollars, tens of thousands of engineers, hundreds of thousands of servers and state-of-the-art data centers to deliver intelligent, distributed and mobile applications based on Machine Learning technology. It seems that there is always a breakthrough of new technology each decade: Mainframe in 1960, Minicomputer in 1970, PC in 1980, Internet in 1990 and Mobile in 2000. Machine Learning has been around for decades. Why is it gaining popularity now? This talk will discuss what machine learning is and how it will impact our daily life and work. DESCRIPTION
able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. 6
data, then use the uncovered patterns to predict future data, or perform other kinds of decision making under uncertainty (such as planning how to make collect more data). -- Machine Learning: A Probabilistic Perspective, Kevin P. Murphy 10
machine learning methods based on learning representations of data. An observation (e.g., an image) can be represented in many ways such as a vector of intensity values per pixel, or in a more abstract way as a set of edges, regions of particular shape, etc. Source: Wikipedia 12
application: in e-commerce, cluster users into groups based on their purchasing behavior, and then to send targeted ads to each group • Discovering latent factors (dimensionality reduction) - application: map 3D to 2D 16 Source: Machine Learning: A Probabilistic Perspective, Kevin P. Murphy
such that y = f(x) where y has a (non linear) relationship with z • This is useful for learning how to act or behave when given occasional reward or punishment signals • e.g. given lots of chess board position (x) and piece to move next (z) pairs, find what piece to move next to eventually win (y) a chess board position (x) 17 Source: Machine Learning: A Probabilistic Perspective, Kevin P. Murphy
Healthcare Search Face Recognition Fingerprint Identification Character Recognition Auto-correct on smart phone Language Translation (Natural Language Processing) 28