报告题目：Deep Machine Learning: A data science perspective introduction with R implementation

报告人：卢祖帝 教授 （英国南安普顿大学）

主持人：李淑惠 博士

报告时间：2020/10/30 周五下午 16:00-17:30

报告地点/形式：线上报告（钉钉平台）

报告人简介：

Prof Zudi Lu joined, as a Professor/Chair in Statistics, in the School of Mathematical Sciences and the Southampton Statistical Sciences Research Institute (S3RI) at University of Southampton, UK, in late 2013. Prior to that, he had worked at several international academic institutions, including the University of Adelaide (2009-2013) and Curtin University (2006-2009) in Australia, the London School of Economics (2003-2006) in the UK, the Academy of Mathematics and Systems Science at Chinese Academy of Sciences (1997-2003) in Beijing, China, and the Universite Catholique de Louvain (1996-1997) in Louvain-la-Neuve, Belgium, after he received his PhD degree from the Chinese Academy of Sciences in 1996. He was a recipient of the Australian Research Council Future Fellowship in its 2010 round, and is an elected member of the International Statistical Institute since 2013.

报告摘要：

Data science is a concept to unify statistics, data analysis and their related methods in order to understand and analyze actual phenomena with data. In the age of big data and artificial intelligence (AI), there is a lot of excitement surrounding the fields of Neural Networks (NN) and Deep Machine Learning (DML), due to numerous well-publicized successes that these systems have achieved in the last few years. The objective of this talk is to provide a simple introduction on some basic aspects of Deep Machine Learning from the data science perspective, with an emphasis on some numerical implementation in R for neural networks that use deep learning algorithms.

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