Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1174
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dc.contributor.authorTang, Jeff-
dc.date.accessioned2026-07-17T11:22:39Z-
dc.date.available2026-07-17T11:22:39Z-
dc.date.issued2008-05-
dc.identifier.isbn978-1-78883-454-4-
dc.identifier.urihttp://hdl.handle.net/123456789/1174-
dc.description.abstractArtificial Intelligence (AI), the simulation of human intelligence in computers, has a long history. Since its official birth in 1956, AI has experienced several booms and busts. The ongoing AI resurgence, or the new AI revolution, started in 2012 with the breakthrough in deep learning, a branch of machine learning that is now the hottest branch of AI because of deep learning, when a deep convolutional neural network (DCNN) won the ImageNet Large-Scale Visual Recognition Challenge with an error rate of only 16.4%, compared to the second best non-DCNN entry with an error rate of 26.2%. Since 2012, improved DCNNbased entries have won the ImageNet challenge every year, and deep learning technology has been applied to many hard AI problems beyond computer vision, such as speech recognition, machine translation, and the game of Go, resulting in one breakthrough after another. In March 2016, Google DeepMind's AlphaGo, built with deep reinforcement learning, beat 18-time human world Go champion Lee Sedol 4:1. At Google I/O 2017, Google announced that they're shifting from mobile-first to AI-first world. Other leading companies such as Amazon, Apple, Facebook, and Microsoft have all invested heavily in AI and launched many AI-powered products.en_US
dc.language.isoenen_US
dc.publisherPackt Publishingen_US
dc.relation.ispartofseries1160518;-
dc.subjectIntelligent Mobile Projects with TensorFlowen_US
dc.titleIntelligent Mobile Projects with TensorFlowen_US
dc.title.alternativeBuild 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pien_US
dc.typeBooken_US
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