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April 10-11, 2018: Training
April 11-13, 2018: Tutorials & Conference
Beijing, CN

In-Person Training
用TensorFlow进行深度学习

Michael Li (The Data Incubator), Season Yang (McKinsey & Company)
Tuesday, April 10 & Wednesday, April 11, 09:00 - 17:00
Location: 多功能厅5A+B(Function Room 5A+B)

Participants should plan to attend both days of this 2-day training course. Platinum and Training passes do not include access to tutorials on Wednesday.

TensorFlow是一个流行的深度学习的工具。我们会介绍TensorFlow的流程图、学习使用它的Python API,并展示它的用处。我们会从简单的机器学习算法开始,然后实现神经网络。我们还会讨论一些真实的深度学习的应用,包括机器视觉、文本处理和生成型网络。

很多AI应用里的深度学习算法的背后都是大型矩阵运算。TensorFlow为这样的运算提供了数据流程图,从而让算法可以很容易地在多个处理器或机器上并行进行。这一特性使得TensorFlow成为实现神经网络和其他深度学习算法理想的环境。本辅导课程将会使用TensorFlow的Python API来介绍和设计TensorFlow里的计算。并以此为基础,进一步介绍目前使用的一些深度学习算法。卷积神经网络可以被用来为机器视觉提供目标识别的能力。循环神经网络(包括长短期记忆架构)可以被用来理解时间序列和语言数据。而生成型网络则让AI应用有能力创造出输出。

About your instructors

Photo of Michael Li

Tianhui Michael Li is the founder and president of the Data Incubator, a data science training and placement firm. Michael bootstrapped the company and navigated it to a successful sale to the Pragmatic Institute. Previously, he headed monetization data science at Foursquare and has worked at Google, Andreessen Horowitz, J.P. Morgan, and D.E. Shaw. He’s a regular contributor to the Wall Street JournalTech CrunchWiredFast CompanyHarvard Business ReviewMIT Sloan Management ReviewEntrepreneurVenture Beat, Tech Target, and O’Reilly. Michael was a postdoc at Cornell Tech, a PhD at Princeton, and a Marshall Scholar in Cambridge.

Photo of Season Yang

Season Yang is an analytics fellow in McKinsey & Company’s risk practice. Previously, Season was a data scientist in residence at the Data Incubator, where he also contributes to curriculum development and instruction, and worked at NASA’s Goddard Space Flight Center, where he studied climate change models with data analysis. Season holds a double bachelor’s degree in applied mathematics and scientific computation and economics from UC Davis and a master’s in applied mathematics from Columbia, specializing in numerical computation.

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