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Synopsis
Neural networks have been a mainstay of artificial intelligence since its earliest days. Now, exciting new technologies such as deep learning and convolution are taking neural networks in bold new directions. In this book, we will demonstrate the neural networks in a variety of real-world tasks such as image recognition and data science. We examine current neural network technologies, including ReLU activation, stochastic gradient descent, cross-entropy, regularization, dropout, and visualization.
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About the Author
Jeff Heaton, PhD, is a computer scientist that specializes in data science and artificial intelligence. Specializing in Python, R, Java and C#, he is an open source contributor and author of more than ten books. His areas of expertise include predictive modeling, data mining, big data, business intelligence, and artificial intelligence. Jeff holds a Master's Degree in Information Management from Washington University and a PhD in computer science from Nova Southeastern University in computer science. He is the lead developer for the Encog Machine Learning Framework open source project, a senior member of IEEE, and a fellow of the Life Management Institute (FLMI).
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- PublisherCreateSpace Independent Publishing Platform
- Publication date2015
- ISBN 10 1505714346
- ISBN 13 9781505714340
- BindingPaperback
- LanguageEnglish
- Number of pages374
- Rating
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Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
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Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
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Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
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Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
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Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks
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