Titlebook: Introduction to Deep Learning Business Applications for Developers; From Conversational Armando Vieira,Bernardete Ribeiro Book 2018 Arman

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Deep Learning: An Overview words, data without labels. They were called . (DBNs) and consisted of staked restrictive Boltzmann machines (RBMs), with each one placed on the top of another. DBNs differ from previous networks since they are generative models capable of learning the statistical properties of data being presented without any supervision.

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omplexities in deploying a Deep Learning platform – in-houseDiscover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotat

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New Research and Future Directionsthe near future, both supervised learning RNNs and reinforcement learning will be greatly scaled up. Current large ANNs have on the order of a billion connections; soon that will be a trillion, at the same price. By comparison, human brains have a trillions of—much slower—connections.

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IntroductionThis chapter will describe what the book is about, the book’s goals and audience, why artificial intelligence (AI) is important, and how the topic will be tackled.