Francois Chollet-Deep Learning with Python
Keras深度学习框架的作者Francois Chollet写的,权威性极强。 Google AI 研究人员,以及颇受欢迎的流行的深度学习库 Keras的作者Francois Chollet,在2017年10月份写下了这本《Deep Learning with Python》
Keras深度学习框架的作者Francois Chollet写的,权威性极强。 Google AI 研究人员,以及颇受欢迎的流行的深度学习库 Keras的作者Francois Chollet,在2017年10月份写下了这本《Deep Learning with Python》
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The use of probability to measure uncertainty and variability dates back hundreds of years. Probability has found application in areas as diverse as medicine, gambling, weather forecasting, and the law.
To summarize, deep learning, the subject of this book, is an approach to AI. Specifically, it is a type of machine learning, a technique that allows computer systems to improve with experience and data. According to the authors of this book, machine learning is the only viable approach to building AI systems that can operate in complicated, real-world environments. Deep learning is a particular kind of machine learning that achieves great power and flexibility by learning to represent the world as a nested hierarchy of concepts, with each concept defined in relation to simpler concepts, and more abstract representations computed in terms of less abstract ones.
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods by Nello Cristianini and John Shawe-Taylor ISBN:0521780195 Cambridge University Press ?2000 (190 pages) This is the first comprehensive introduction to SVMs, a new generation learning system based on recent advances in statistical learning theory; it will help readers understand the theory and its real-world applications.