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

Artificial Intelligence Training

All training courses take place 9:00 – 17:00, Tuesday, April 10 through Wednesday, April 11. In order to maintain a high level of hands-on learning and instructor interaction, each training course is limited in size. Participants should plan to attend both days of this 2-day training course. Training passes do not include access to tutorials on Wednesday.

Tuesday, April 10

Add to your personal schedule
09:00 - 17:00 Tuesday, April 10 & Wednesday, April 11
Location: 多功能厅5A+B(Function Room 5A+B)
Michael Li (The Data Incubator), Season Yang (McKinsey & Company)
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。 Read more.
Add to your personal schedule
09:00 - 17:00 Tuesday, April 10 & Wednesday, April 11
Location: 多功能厅6A+B (Function Room 6A+B)
Secondary topics:  深度学习(Deep Learning), 金融服务 (Financial Services)
Chia Wei Lim (Skymind), Wang Feng (Skymind)
Average rating: ***..
(3.00, 2 ratings)
在分析时间序列或者序列数据方面循环神经网络(RNN)已经被证明是非常有效的,那么在实际的案例中如何才能把循环神经网络(RNN)的优点发挥出来呐?这里将演示如何用Deeplearning4j框架构建循环神经网络(RNN)来解决时间序列的问题。 Read more.
Add to your personal schedule
09:00 - 17:00 Tuesday, April 10 & Wednesday, April 11
Location: 多功能厅3A+B(Function Room 3A+B) Level: Intermediate
Jike Chong (Tsinghua University | Acorns), 黄铃 (Tsinghua University), Zoe Chen (eCreditPal.com)
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。 Read more.