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English | PDF | 2011 | 93 Pages | ISBN : N/A | 0.4 MB

"A First Encounter with Machine Learning"

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English | PDF | 2011 | 93 Pages | ISBN : N/A | 0.4 MB

Machine learning is a relatively recent discipline that emerged from the gen- eral field ofartificial intelligenceonlyquiterecently. To buildintelligentmachines researchers realized that these machines should learn from and adapt to their en- vironment. It is simply too costly and impractical to design intelligent systems by first gathering all the expert knowledge ourselves and then hard-wiring it into a machine. For instance, after manyyears ofintenseresearch thewe can now recog- nize faces in images to a high degree accuracy. But the world has approximately 30,000 visual object categories according to some estimates (Biederman). Should we invest the same effort to build good classifiers for monkeys, chairs, pencils, axes etc. or should we build systems to can observe millions of training images, some with labels (e.g. in these pixels in the image correspond to a car) but most of them without side information?
Although there is currently no system which can recognize even in the order of 1000 object categories (the best system can get
about 60% correct on 100 categories), the fact that we pull it off seemingly effort- lessly serves as a "proof of concept" that it can be done. But there is no doubt in my mind that building truly intelligent machines will involve learning from data.


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