机器学习及其实践应用

所属专题:深度培训

所属领域:

嘉宾 : Bin Xu | FacebookSoftware Engineer Manager

会议室 : 深圳·华侨城洲际酒店 马德里3

讲师介绍

培训讲师:Bin Xu

Facebook Software Engineer Manager

Bin Xu is an Software Engineer Manager at Facebook. He leads the Machine Learning team and Infra team in Business Integrity. His teams ensure the trustworthiness of connections between people and businesses; such as Ads, Marketplace, Groups, Pages, etc. Prior to his current position, he was a Principle Machine Learning Engineer Manager at Microsoft, led a team to develop cloud security solutions, and implemented anomaly detection to protect customer identity, data and applications. Before joining Microsoft, he was with Amazon for 10 years, leading the Applied Scientist teams on transaction risk management.

Bin received his Ph.D. in Statistics, M.S. in Computer Science from State University of New York at Stony Brook; and  his M.S. and B.Sc. in Computer Science from Wuhan University.

参考翻译:徐斌目前在Facebook带领Business Integrity的机器学习团队和机器平台架构团队,主要任务是确保Facebook的用户和Facebook上所有商业业务之间的诚信沟通。这些商业业务存在于广告、市场、社团/群组、粉丝专页等等。在进入Facebook前,徐斌在Microsoft担任首席机器学习工程经理,带领技术团队开发云安全解决方案,实现对异常现象的检测,并保护客户在云中的身份、数据和应用的安全。此前,徐斌在Amazon工作10年,率领多个应用科学家团队处理交易风险管理工作。

徐斌在美国纽约州立大学石溪分校获得计算机科学硕士学位和统计学博士学位,在武汉大学获得计算机的本科和硕士学位。

议题介绍

地点:深圳·华侨城洲际酒店 马德里3
所属专题:深度培训
所属领域:

演讲:机器学习及其实践应用

1. What's Machine Learning
2. ML applications in life
3. Course Outlies
4. Building a ML 
    a. problem and steps 
    b. Feature Engineering
5. Supervised Learning
    a. classification [*]
        i. Logistic Regression
        ii. Decision Tree
        iii. Random Forest
        iv. GBT
    b. Regression [*]
        i. Linear Regression
        ii. RF regression
    c. Deep Learning [*]
        i. Neural Network
        ii. CNN
        iii. RNN
    d. Model Performance
        i. ROC
        ii. Precision & Recall
6. Unsupervised/Semi-supervised Learning [*]
7. Other ML Technologies (backup, e.g. Personalization, Forecasting)
8. ML platform design in industry
    a. platform design
    b. ML org structure
    c. ML Infra requirement
    d. ML performance stability
9. ML Applications in high-profile companies, e.g. Facebook, Microsoft and Amazon, etc.
10. Q&A
 
[*] practice in R or python

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