week1.2 Who we are

Carlos Guestrin(gentleman)

  • Amazon Professor of Machine Learning in Computer Science.
  • Got undergraduate degree ifrom University of Sao Paulo in Brazil.
  • Got PhD from Stanford in computer science.
  • Working in machine learning for a long time to make decisions, to process data from distributed sensors.

Emily Fox(lady)

  • Amazon Professor of Machine Learning in Statistics.
  • Stuied in MIT for nine years, get PHD in electrical engineering and computer science.
  • Did a postdoc in statistics at Duke.
  • Focus on important temporal structure data, such as large collections of time series.

summerize

?We're really gonna be focused on for applications first, understanding how machine learning has impact and then digging in and understanding how those methods are built and how they can be useful.

Amazon Professor(3) = 3
machine learning(16) = 16
qualification(3) = 3
self-taught(2) = 2
scale(3 + 2 lots of data) = 5

two professor:
??1.1 work on theoretical algorithms for what's called planning under uncertainty for making decisions using machine learning.
??1.2 large-scale machine learning.
?
??2.1 how to scale up to really high dimensional or large collections of time series, especially when they have very complex dynamics.(temporal)
??2.2 how to make inferences online as data is streaming in.

broad(3) = 3 broad audience & broad idea

最后編輯于
?著作權(quán)歸作者所有,轉(zhuǎn)載或內(nèi)容合作請聯(lián)系作者
【社區(qū)內(nèi)容提示】社區(qū)部分內(nèi)容疑似由AI輔助生成,瀏覽時請結(jié)合常識與多方信息審慎甄別。
平臺聲明:文章內(nèi)容(如有圖片或視頻亦包括在內(nèi))由作者上傳并發(fā)布,文章內(nèi)容僅代表作者本人觀點,簡書系信息發(fā)布平臺,僅提供信息存儲服務(wù)。

相關(guān)閱讀更多精彩內(nèi)容

友情鏈接更多精彩內(nèi)容