O’REILLY、INTEL AI 主办
Put AI to work
2018年4月10-11日:培训
2018年4月11-13日:辅导课 & 会议
北京,中国
 
紫金大厅B(Grand Hall B)
Add 用于自动驾驶的机器学习 to your personal schedule
09:00 用于自动驾驶的机器学习 Erran Li (Uber ATG)
Add 人工智能和金融科技:量化金融信用与欺诈风险的评估  to your personal schedule
13:30 人工智能和金融科技:量化金融信用与欺诈风险的评估 黄铃 (慧安金科(北京)科技有限公司)
报告厅(Auditorium)
Add Getting up and running with TensorFlow to your personal schedule
09:00 Getting up and running with TensorFlow Yufeng Guo (Google)
Add Deep reinforcement learning tutorial to your personal schedule
13:30 Deep reinforcement learning tutorial Arthur Juliani (Unity Technologies)
多功能厅2(Function Room 2)
Add 基于Apache Spark及BigDL构建高级数据分析 to your personal schedule
09:00 全天教学辅导课 基于Apache Spark及BigDL构建高级数据分析 Zhichao Li (Intel)
多功能厅8A+8B(Function Room 8A+8B)
Add Bringing AI into the enterprise to your personal schedule
09:00 DAY-LONG TUTORIAL Bringing AI into the enterprise Kristian Hammond (Narrative Science)
12:30 午餐 (Lunch) | Room: 彩虹厅及国际厅 (Rainbow Room & Ballroom)
07:30 早咖啡服务 (Morning Coffee and Tea Service) | Room: 1楼序厅(1st Floor Foyer)
10:30 上午茶歇 (Morning Break) | Room: 1楼序厅(1st Floor Foyer)
15:00 下午茶歇 (Afternoon Break) | Room: 1楼序厅(1st Floor Foyer)
09:00-12:30 (3h 30m) 实施人工智能 (Implementing AI), 模型与方法 (Models and Methods) 运输与物流 (Transportation and Logistics)
用于自动驾驶的机器学习
Erran Li (Uber ATG)
尽管最近人工智能等领域取得了很多的进展,但自动驾驶里的主要问题(不管是基础研究还是工程应用上的挑战)离完全被解决还有很大的距离。Erran Li将会探索自动驾驶所用的机器学习的基础,并讨论目前相关工作的进展。
13:30-17:00 (3h 30m) 与人工智能交互 (Interacting with AI), 实施人工智能 (Implementing AI)
人工智能和金融科技:量化金融信用与欺诈风险的评估
黄铃 (慧安金科(北京)科技有限公司)
您想了解金融企业是怎样利用大数据和人工智能技术来画像个人行为并检测欺诈用户的吗?互联网金融幕后的量化分析流程是怎么杨的?个人信用是怎样通过大数据被量化的?在实践过程中,机器学习算法的应用存在着哪些需要关注的方面?怎样通过图谱分析来融合多维数据,为我们区分正常用户和欺诈用户? 这套辅导课基于清华大学交叉信息研究院2017年春天新开设的一门"量化金融信用与风控分析”研究生课。其中会用LendingClub的真实借贷数据做为案例,解说一些具体模型的实现。
09:00-12:30 (3h 30m) 实施人工智能 (Implementing AI), 模型与方法 (Models and Methods), 英文讲话 (Presented in English) 深度学习(Deep Learning)
Getting up and running with TensorFlow
Yufeng Guo (Google)
Yufeng Guo walks you through training a machine learning system using popular open source library TensorFlow, starting from conceptual overviews and building all the way up to complex classifiers. Along the way, you'll gain insight into deep learning and how it can apply to complex problems in science and industry.
13:30-17:00 (3h 30m) 实施人工智能 (Implementing AI), 模型与方法 (Models and Methods), 英文讲话 (Presented in English) 增强学习(Reinforcement Learning)
Deep reinforcement learning tutorial
Arthur Juliani (Unity Technologies)
Recently, computers have been able to learn to play Atari games, Go, and first-person shooters at a superhuman level. Underlying all these accomplishments is deep reinforcement learning. Arthur Juliani offers a deep dive into reinforcement learning, from the basics using lookup tables and GridWorld all the way to solving complex 3D tasks with deep neural networks.
09:00-17:00 (8h) 实施人工智能 (Implementing AI), 模型与方法 (Models and Methods) 深度学习(Deep Learning)
基于Apache Spark及BigDL构建高级数据分析
Zhichao Li (Intel)
从这个教学课程里,学员将会学到如何应用深度学习(最先进的机器学习技术)到他们的Apache Spark驱动的大数据工作任务里
09:00-17:00 (8h) 英文讲话 (Presented in English) 传媒、广告、娱乐 (Media, Advertising, Entertainment), 制造业与工业自动化 (Manufacturing and Industrial Automation), 设计AI平台(Designing AI platforms), 金融服务 (Financial Services)
Bringing AI into the enterprise
Kristian Hammond (Narrative Science)
Even as AI technologies move into common use, many enterprise decision makers remain baffled about what the different technologies actually do and how they can be integrated into their businesses. Rather than focusing on the technologies alone, Kristian Hammond provides a practical framework for understanding your role in problem solving and decision making.
12:30-13:30 (1h)
Break: 午餐 (Lunch)
07:30-09:00 (1h 30m)
Break: 早咖啡服务 (Morning Coffee and Tea Service)
10:30-11:00 (30m)
Break: 上午茶歇 (Morning Break)
15:00-15:30 (30m)
Break: 下午茶歇 (Afternoon Break)