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网络公开课资源 ——关注CS/AI/Math

發布時間:2025/3/21 ChatGpt 59 豆豆
生活随笔 收集整理的這篇文章主要介紹了 网络公开课资源 ——关注CS/AI/Math 小編覺得挺不錯的,現在分享給大家,幫大家做個參考.

當當當當~請看這個網址 -?http://www.class-central.com/?- 它是一個列表,列出幾大在線課程網站(有英文字幕和習題就是好啊^^)的課程表 (比網易云課堂更原汁原味哦,現在也可以看課程圖譜,學累了可以輕松幾分鐘?,還有浙大的計算機中的數學)

  • Stanford's Coursera?-?http://www.coursera.org/?
  • Edx?-?https://www.edx.org?
  • Udacity(也是Stanford教授參與創建的)-?http://www.udacity.com/?
  • Caltech(California Institute of Technology) -?http://work.caltech.edu/telecourse.htmlMachine Learning course,?April 3rd till May 31st 2012?

這些都是新課,在網上正在上的課。之前的MIT OCW(數學課很厲害,CS在這里)是已經結束了的課,有Multimedia content標志的課值得一聽。

這些新課好多都是CS的:

最近剛結束的有Introduction to AI?,?Introduction to Databases(SQL,OLAP,NoSQL) and?Introduction to Machine Learning?

正on live的有Probabilistic Graphical Models,?Natural Language Processing,?Design and Analysis of Algorithms I,CS 101: Building a Search Engine

即將開始的有Introduction to Machine Learning,?Learning from Data ( Introductory Machine Learning course),Computer Vision,?CS212 - The Design of Computer Programs,


?

Stanford?engineering everywhere -?http://see.stanford.edu/see/courses.aspx?

  • artificial intelligence|natural language processing?
    http://see.stanford.edu/see/lecturelist.aspx?coll=63480b48-8819-4efd-8412-263f1a472f5a?翻譯
  • artificial intelligence|machine learning?
    http://see.stanford.edu/see/courseinfo.aspx?coll=348ca38a-3a6d-4052-937d-cb017338d7b1?網易翻譯版
Some mathematical details and derivations have been omitted in this course, since this is CS229a -?Applied Machine Learning?at Stanford. The course with complete Mathematical Depth ( but lesser emphasis on practical application ) is CS229 -?Machine Learning. In case you are interested in more algorithms, reinforcement learning and the mathematical derivation for some of the methods, you might find it interesting and useful to take a look at the regular CS229 notes. http://cs229.stanford.edu/materials.html The problem sets are also mathematical and challenging. Standford wiki for?unsupervised learning http://ufldl.stanford.edu/wiki/index.php/UFLDL_Tutorial?


Harvard?university extension school -http://www.extension.harvard.edu/courses/subject/computer-science

http://www.extension.harvard.edu/open-learning-initiative/math-sets-probability



Machine Learning? -Spring 2011

Carnegie Mellon University,大名鼎鼎的?Tom Mitchell?

??

http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml

with videos, assignments, exams and solutions (also slides, exercises and exams available for the previous 9 installments of the course). http://www.cs.cmu.edu/~avrim/ML09/index.html It's <machine learning?theory>, focusing on theoretical aspects of machine learning, I think it may consider as a advanced theory foundation to machine learning course.

?

Google Code University

https://code.google.com/edu/?

  • Python Course(有個Python學習社區)
  • C++ Course
  • Curriculum Search

Top Viewed Courses

  • Google's Python Class
  • Introduction to Distributed System Design
  • Introduction to Parallel Programming and MapReduce

想去Google的絕對不能錯過(原諒我用這么大大的logo ^^)

  • Programming Languages??
    • Google's Python Class?|?Understanding Python?國內下載地址?翻譯
    • Google's C++ Class
  • Algorithms
    • Algorithms?-Princeton
    • Analysis of Algorithms?-Standford
    • Three Beautiful Quicksorts
  • Distributed Systems?
    • Introduction to Distributed System Design
    • Introduction?to Parallel Programming and MapReduce
  • Tools 101
    • Introduction to Databases and MySQL
    • Linux
      • Basic Linux Commands
      • Linux Ownership and Permissions
      • Text Processing with Grep
      • Greppin' in the GNU World Lab

Some of the?advanced machine learning?related presentations can be found at videolectures.net?http://videolectures.net/Top/Computer_Science/Machine_Learning/ Machine Learning?Summer School 2009, organized by Cambridge, I found a lot of great ML scientists here given lectures, such as Christopher Bishop, David Blei, and Michael I. Jordan. Unfortunately my network is a little bad and cannot download from videolectures http://videolectures.net/mlss09uk_cambridge Lectures from?Machine Learning?Summer School 2011 - Bordeaux?
http://videolectures.net/mlss2011_bordeaux/ p.s. Checked the archives, there are some resources from videolectures.net already, but it looks mlss2011_bordeaux hasn't been posted yet.
更多的好網站可以看quora上的這個各抒己見 http://www.quora.com/Machine-Learning/What-are-some-good-resources-for-learning-about-machine-learning-Why

其他一些課程合輯:

http://www.m-e-e-t.com/course/show_subject/24

http://www.douban.com/group/opencourse/

http://www.kaifangke.com/forum.php?mod=forumdisplay&fid=130?



IntelligentTrading blog http://intelligenttradingtech.blogspot.com for those interested in?applications of machine learning to trading! Mostly practical examples for the laymen(非專業人員), pretty well explained. Some other basic course materials http://www.autonlab.org/tutorials/ These contains statistical?Data mining?tutorials from Andrew Moore?
Another tutorial http://www.willamette.edu/~gorr/classes/cs449/intro.html Notations are different, might have to map it properly.
一些數學: Matrix http://www.sosmath.com/matrix/matrix.html?

Advance algebra http://www.purplemath.com/modules/ordering.htm?

Pre?Calculus?- don't know if this is helpful for the class http://www.youtube.com/watch?v=CtRAHmeWSC0&feature=relmfu Another good resource is Gil Strang's excellent MIT?Linear Algebra?course http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010 An interesting (and funny) lecture discussing limitations of the?neural networks:http://www.youtube.com/user/GoogleTechTalks#p/search/0/AyzOUbkUf3M
Scientific books and papers on?AI. Interesting, but advanced:http://www.intechopen.com/subject/compu

ter-and-information-science/artificial-intelligence/ The?Matrix and Quaternions?FAQ?
http://www.flipcode.com/documents/matrfaq.html
??
home?|?blog
  • physics
  • chemistry
  • computer science
  • mathematics
  • faculty mix

搜索引擎原理與系統架構

??? 本次課程講授的內容包括搜索引擎處理的主要問題,以及搜索引擎的主要框架與模塊構成。將幫助同學們熟悉搜索引擎的主要設計思路,以及在此基礎上的模塊劃分與架構考慮。pdf

海量數據處理

??? 響應搜索需求,為用戶高效找到目標網頁,在貼吧、知道、音樂等產品中為用戶推薦精彩內容,幫助廣告商和網站進行精確預測,支持語音自動搜索和導航,進行中英語言的自動翻譯……這些服務的背后,是百度對海量數據和用戶行為的深刻理解。本次課程將講解百度海量數據處理的機制和相關技術要點。

互聯網行業的軟件工程師修煉之道

??? 支撐百度十年快速發展的,歸根到底是人。百度是一個工程師文化為主導的互聯網公司,百度工程師六大意識是優秀工程師的經驗總結。本課程將結合實際工作case分享六大意識,特別是如何成為作為一名優秀的工程師,以及個人需要具備必備哪些軟技能。講師還將就在校學生如何結合目前的專業技術課程更好地積累和儲備知識、發展個人能力,給出建議。ppt

百度開放云

??? 本堂課將詳細介紹百度開放云平臺的特點和應用案例。

中國Web App開發者研究報告-周云鵬

??? DCCI互聯網數據中心分析師周云鵬對中國Web App開發者研究報告進行了分享。此次調研針對Web App生態發展情況,研究開發者對開放平臺的認知、看法和期望。此外,周云鵬還對國內主要Web App應用開放平臺的特征優勢進行了總結。

如何基于開放平臺實現營銷創新-肖鵬

??? 阿普創新團隊創始人摻摻以“平臺需要內容,品牌掌握優質內容”來說明應用、平臺以及企業品牌三者之間的關系。他認為目前通過百度開放平臺推廣具有以下優勢:低成本、搜索導向產生持續效果、內容親和度、長尾關鍵詞帶來精準用戶、平臺依托保障大流量。

from:?http://www.cnblogs.com/wei-li/p/ScaldingFirstSight3.html

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