互动吧
活动配套服务
发布活动
  • 会员专享
  • 优惠券
  • 公众号
    微信公众号

    互动吧服务号

    智能提醒助手

    实时获取最新通知

    吧友福利社

    吧友福利社

    互动吧福利专号

    发放免费票、福利好物

  • 小程序
    小程序

    互动吧小程序

    随时随地找活动

    扫码即用免安装

  • 互动吧App
    互动吧App

    互动吧App

    优惠红包享不停

    活动管理一手掌控

  • 成为VIP主办方
修改本活动
北京互动吧 互动吧 北京互联网 互动吧 北京人工智能 互动吧 OReilly和Intel人工智能大会2019北京站
互动吧-OReilly和Intel人工智能大会2019北京站

OReilly和Intel人工智能大会2019北京站

{{shopName|html}}

该主办方未在互动吧平台认证,请您谨慎报名

该主办方已完成互动吧个人认证企业认证组织认证
真实姓名
{{authName}}
证件号码
{{authCode}}
认证时间
{{authTime}}完成认证,每年互动吧都会对其资料进行审核
互动吧认证申明
个人认证是互动吧对主办方帐号背后运营主体真实身份的认证,不代表互动吧对主办方所使用名称、介绍及真实营业情况的认证。
企业全称
{{authName}}
工商执照注册号/统一社会信用代码
{{authCode}}
认证时间
{{authTime}}完成认证,每年互动吧都会对其资料进行审核
互动吧认证申明
企业认证是互动吧对主办方帐号背后运营主体真实身份的认证,不代表互动吧对主办方所使用名称、介绍及真实营业情况的认证。
组织机构名称
{{authName}}
组织机构代码/统一社会信用代码
{{authCode}}
认证时间
{{authTime}}完成认证,每年互动吧都会对其资料进行审核
互动吧认证申明
组织认证是互动吧对主办方帐号背后运营主体真实身份的认证,不代表互动吧对主办方所使用名称、介绍及真实营业情况的认证。
我也要认证 >
{{info_hits}} {{info_share}} {{favorite_count}}
此活动来自活动节优品
更多场次
{{list.name}}
全部票种

该活动{{partyStateMark}}

关注主办方,不错过主办方任何一个活动。

该主办方未在互动吧平台认证,请您谨慎报名

该主办方已完成
互动吧个人认证企业认证组织认证
真实姓名
{{authName}}
证件号码
{{authCode}}
认证时间
{{authTime}}完成认证,每年互动吧都会对其资料进行审核
互动吧认证申明
个人认证是互动吧对主办方帐号背后运营主体真实身份的认证,不代表互动吧对主办方所使用名称、介绍及真实营业情况的认证。
企业全称
{{authName}}
工商执照注册号/统一社会信用代码
{{authCode}}
认证时间
{{authTime}}完成认证,每年互动吧都会对其资料进行审核
互动吧认证申明
企业认证是互动吧对主办方帐号背后运营主体真实身份的认证,不代表互动吧对主办方所使用名称、介绍及真实营业情况的认证。
组织机构名称
{{authName}}
组织机构代码/统一社会信用代码
{{authCode}}
认证时间
{{authTime}}完成认证,每年互动吧都会对其资料进行审核
互动吧认证申明
组织认证是互动吧对主办方帐号背后运营主体真实身份的认证,不代表互动吧对主办方所使用名称、介绍及真实营业情况的认证。
我也要认证 >

{{pub_count}}

活动

{{fansCount}}

粉丝

{{shopDesc|html}}进店 >

Ta组织活动太忙,还没腾出空写简介进店 >

活动详情


人工智能大会把硅谷带到中国

人工智能北京大会是无与伦比的世界先锋创新者盛会。极度聚焦于技术内容和商业应用的交融,吸引了世界各地的热爱人工智能人士。大会有4天信息满满的内容,包括实用性的分会场议题,深度培训课程,极具启发性的主题演讲,以及难得的思想交流与碰撞的社交机会。

人工智能大会:将人工智能在工作中用起来

本次大会的独特之处在于将重点放在应用人工智能——弥合人工智能研究领域与产业商业应用之间的差距。

只有本次北京人工智能大会才将硅谷和中国融合在一起,创造一次全球人工智能专家难得的相聚。讲师为来自各公司人工智能专家,包括百度、谷歌、eBay、Bonsai、Uber、微软、阿里巴巴、亚马逊、SAS、Unity、SalesForce、IBM、伯克利、斯坦福及牛津大学——仅为部分公司。

无论你的关注点在哪里都将在本次人工智能大会上找到:

  • 企业中的人工智能:执行简报,案例研究及用例,行业特定应用

  • 人工智能对商业及社会的影响:自动化,安全,规范

  • 实施人工智能项目:应用,工具,架构,安全

  • 与人工智能交互:设计,指标,产品管理,机器人

  • 模型及方法:增强及机器学习,TensorFlow,深度学习,GAN,自然语言处理及理解,语音识别,计算机视觉


人工智能培训课程

将自己沉浸在两天针对关键主题的课程中。培训课程安排在6月18-19日进行,控制班级规模以保证参会者的学习体验(包括与讲师互动)。

课程一  量化互联网金融信用与反欺诈风控

课程二  Deep Learning with TensorFlow

课程三  Deep Learning with PyTorch

课程四  Professional Kafka development


会议精彩内容节选

                                                  

Deep Learning with PyTorch

O'Reilly和Intel人工智能大会2019北京站

Rich Ott (The Data Incubator)

PyTorch is a machine learning library for Python that allows users to build deep neural networks with great flexibility. Its easy to use API and seamless use of GPUs make it a sought after tool for deep learning. This course will introduce the PyTorch workflow and demonstrate how to use it. Students will be equipped with the knowledge to build deep learning models using real-world datasets. 



Deep Learning with TensorFlow

O'Reilly和Intel人工智能大会2019北京站

Season Yang (McKinsey & Company)

The TensorFlow library provides for the use of computational graphs, with automatic parallelization across resources. This architecture is ideal for implementing neural networks. This training will introduce TensorFlow's capabilities in Python. It will move from building machine learning algorithms piece by piece to using the Keras API provided by TensorFlow with several hands-on applications.



量化互联网金融信用与反欺诈风控

_@user_218421.jpg

Jike Chong (Tsinghua University | Acorns)

O'Reilly和Intel人工智能大会2019北京站

黄铃 (Tsinghua University)

O'Reilly和Intel人工智能大会2019北京站

陈薇 (排列科技)

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。


A practical guide towards explainability and bias Evaluation in machine learning

Alejandro Saucedo (The Institute for Ethical Ai & Machine Learning)

Undesired bias in machine learning has become a worrying topic due to the numerous high profile incidents. In this talk we demystify machine learning bias through a hands-on example. We'll be tasked to automate the loan approval process for a company, and introduce key tools and techniques from latest research that allow us to assess and mitigate undesired bias in our machine learning models.


Design thinking for AI

Chris Butler (Philosophie)

Purpose, a well-defined problem, and trust from people are important factors to any system, especially those that employ AI. Chris Butler leads you through exercises that borrow from the principles of design thinking to help you create more impactful solutions and better team alignment.


基于深度学习的时间序列预测 (Deep learning for time series forecasting)

Yijing Chen (Microsoft)


Dmitry Pechyoni (Microsoft)


Angus Taylor (Microsoft)


Vanja Paunic (Microsoft)


Henry Zeng (Microsoft)

Almost every business today uses forecasting to make better decisions and allocate resources more effectively. Deep learning has achieved a lot of success in computer vision, text and speech processing, but has only recently been applied to time series forecasting. In this tutorial we show how and when to apply deep neural networks to time series forecasting. The tutorial will be in CHN and EN.



云服务加速人工智能创新(Accelerate innovations with AI in the cloud)

_@user_349775.jpg

Long Wang (Tencent)

We all know that Cloud is the best place to use new technologies. Long Wang examines what's happening for AI in the cloud. How does AI in the cloud accelerate the innovations in the industry? What's mostly possible? What's still on the way? How does cloud help?



Building reinforcement learning models and AI applications with Ray

Richard Liaw (UC Berkeley RISELab)

Ray is a general purpose framework for programming your cluster. We will lead a deep dive into Ray, walking you through its API and system architecture and sharing application examples, including several state-of-the-art AI algorithms.



领英基于Spark和TensorFlow的大规模AI基础架构

_@user_244112.jpg

Min Shen (LinkedIn)

领英公司的几乎所有产品都离不开基于海量数据和大规模数据运算的机器学习模型。怎样构建一个稳定,高效,和易用的人工智能基础架构,越来越成为一个核心的问题。 这个演讲会先介绍领英大数据团队是怎样在5年的时间里演进这个基础架构,从开始的完全基于Spark的系统,到现在Spark+TensorFlow的环境。 我们还会重点介绍近期解决的技术挑战,来应对接近500PB数据和将近6亿会员的巨大经济图谱。这些挑战包括大规模重量级的深度学习模型,Spark的调优,以及在机器学习生产线中连接不同的步骤(数据准备,模型构建,模型训练,在线inference)。 最后我们会介绍我们近期一些成功的深度学习案例,以及团队在AI基础架构上未来2~3年的计划和愿景。



Efficient deep learning for the edge

Bichen Wu (UC Berkeley)

The success of deep neural networks is attributed to three factors: stronger computing capacity, more complex neural networks, and more data. These factors, however, are usually not available with the edge applications as autonomous driving, AR/VR, IoT, and so on. In this talk we discuss how we apply AutoML, SW/HW codesign, domain adaptation to solve these problems.




The Future of Machine Learning is Tiny

_@user_321129.jpg

Pete Warden (Google)

There are over 250 billion embedded devices in the world. On-device machine learning gives us the ability to turn wasted data into actionable information, and will enable a massive number of new applications over the next few years. Pete Warden digs into why embedded machine learning is so important, how it can be implemented on existing chips, and some of the new uses it will unlock.



Hacking humans made easy: Signal processing + AI + video

David Maman (Binah.ai)

Zero-day attacks. IoT-based botnets. Cybercriminal AI v. cyberdefender AI. While these won’t be going away, they aren’t the biggest worry we have in cybercrime. Hacking humans is. The combination of mere minutes of video, signal processing, remote heart rate monitoring, AI, machine learning, and data science can identify a person’s health vulnerabilities, which evildoers can make worse.



Exciting new features in TensorFlow 2.0

Tiezhen Wang (Google)

TensorFlow 2.0 is a major milestone with a focus on ease of use. This talk will give a in depth introduction to the new exciting features and best practices. Topics such as distributed strategies and edge deployment (TensorFlow Lite and TensorFlow.js) will also be covered.



自动机器学习(Automated machine learning)技术的实践与应用

Hui Xue (微软亚洲研究院)

人工智能在过去的几年里飞速发展,但是机器学习的实践和应用需要消耗一定的人力和时间。例如,如何去做特征选择,如何设计一个适合该任务的神经网络模型等等。而自动机器学习技术,可以帮助开发者和机器学习实战者,缩短开发周期,提高效率。我们的介绍主要包括:自动机器学习技术的进展;我们开源的自动机器学习开源库Neural Network Intelligence; 如何利用自动机器学习的技术,在产品和应用上提高效率,节省所需的时间和缩短周期。我们会在最后一部分,分享一些利用自动特征选择,自动参数调整以及模型架构搜索上的成功案例。




The unreasonable effectiveness of transfer learning on natural language processing

David Low (Pand.ai)

Transfer Learning has been proven to be a tremendous success in the Computer Vision field as a result of ImageNet competition. In the past months, the Natural Language Processing field has witnessed several breakthroughs with transfer learning, namely ELMo, Transformer, ULMFit and BERT. In this talk, David will be showcasing the use of transfer learning on NLP application with SOTA accuracy.



The future of machine learning is decentralized

Alex Ingerman (Google)

Federated Learning is the approach of training ML models across a fleet of participating devices, without collecting their data in a central location. Alex Ingerman introduces Federated Learning, compares the traditional and federated ML workflows, and explores the current and upcoming use cases for decentralized machine learning, with examples from Google's deployment of this technology.




AI and Systems at RISELab

_@user_281655.jpg

Ion Stoica (UC Berkeley)

In this talk, I will describe a few projects at the intersection of AI and Systems that we are developing at RISELab, UC Berkeley. The RISELab is the successor of AMPLab, where several highly successful open source projects, including Apache Spark and Apache Mesos, were de


Bringing research and production together with PyTorch 1.0

Joseph Spisak (Facebook)

Learn how PyTorch 1.0 enables you to take state-of-the-art research and deploy it quickly at scale in areas from autonomous vehicles to medical imaging. We'll deep dive on the latest updates to the PyTorch framework including TorchScript and the JIT compiler, deployment support, the C++ interface. We will also cover how PyTorch 1.0 is utilized at Facebook to power AI across a variety of products.


AI and retail

_@user_180950.jpg

Mikio Braun (Zalando SE)

Taking a look at Zalando and the retail industry we will explore how AI is redefining the way e-commerce sites interact with the customer to create a personalized experience that strives to make sure customers will find what they want when they need it.



Designing Computer Hardware for Artificial Intelligence

_@user_346147.jpg

Michael James (Cerebras)

Artificial Intelligence is defining a new generation of computer technology with applications that blur boundaries between intuition, art, and science. We will discuss the fundamental drivers of computer technology, survey the landscape of AI hardware solutions, and explore the limits of what is possible as new computer platforms emerge.


为什么说人工智能和云计算乃天作之合?(Why do we say AI Should be Cloud Native?)

_@user_323348.jpg

Yangqing Jia (Facebook)

The recent years of AI has grown out of labs and created a transformative power for a vast range of industries. But, while we take it for granted that AI and Cloud come hand in hand, I'll show you an argument one step further: AI should be Cloud Native.





更多精彩议题内容可搜索AI大会或人工智能大会,进入官网查看详情:https://ai.oreilly.com.cn/ai-cn

已报名 ({{join_total_num}})其中{{join_unpay_num}}人正在支付

还木有人报名,快来成为活动第一人吧!

正在加载...
成为VIP主办方,即可去除以下广告 马上成为VIP
  • 为你推荐

加载中

该主办方未在互动吧平台认证,请您谨慎报名

该主办方已完成互动吧个人认证企业认证组织认证
真实姓名
{{authName}}
证件号码
{{authCode}}
认证时间
{{authTime}}完成认证,每年互动吧都会对其资料进行审核
互动吧认证申明
个人认证是互动吧对主办方帐号背后运营主体真实身份的认证,不代表互动吧对主办方所使用名称、介绍及真实营业情况的认证。
企业全称
{{authName}}
工商执照注册号/统一社会信用代码
{{authCode}}
认证时间
{{authTime}}完成认证,每年互动吧都会对其资料进行审核
互动吧认证申明
企业认证是互动吧对主办方帐号背后运营主体真实身份的认证,不代表互动吧对主办方所使用名称、介绍及真实营业情况的认证。
组织机构名称
{{authName}}
组织机构代码/统一社会信用代码
{{authCode}}
认证时间
{{authTime}}完成认证,每年互动吧都会对其资料进行审核
互动吧认证申明
组织认证是互动吧对主办方帐号背后运营主体真实身份的认证,不代表互动吧对主办方所使用名称、介绍及真实营业情况的认证。
我也要认证 >

{{pub_count}}

活动

{{fansCount}}

粉丝

{{shopDesc|html}}进店 >

Ta组织活动太忙,还没腾出空写简介进店 >

该主办方其他进行中的活动
精选活动
  • {{selectlist.title}}
    {{selectlist.infoDate}}
    {{selectlist.priceWithSign}} {{selectlist.plusDiscountPriceRange}} {{selectlist.highlight}}
查看更多 加载中...
取消关注
确定取消关注吗?
取消关注后将无法再关注列表查看Ta的动态

联系Ta

扫码下载互动吧App,马上进行在线沟通

电话咨询: {{joinMobile}} 仅参与此活动用户可见。

在线咨询: 安装互动吧App,马上进行在线沟通。

服务合作: 仅本地合作服务商可见。

服务合作: {{supplierMobile}}

你将要打开一个非互动吧页面,建议不要在该网页输入互动吧帐号、银行资料等隐私信息。

取消关注
确定取消关注吗?
取消关注后将无法再关注列表查看Ta的动态
提示
确定删除本条讨论?
讨论删除后,将不可恢复,您确定继续删除吗?
在线客服
  • 广告合作,请拨
    18516929350

    互动吧广告合作微信

    ID:hdbwudaozi

  • 品牌合作,请拨
    18515087972

    互动吧品牌合作微信

    ID:Mr-haoyang

  • 互动吧服务号合作,请拨
    13292611220

    互动吧服务号合作微信

    ID:hdb-ysx