Mouse bindings:
camera: Button 1 - rotate
Button 2 - pan
Button 3 - zoom
ctrl-Button 1 - spin
actor: Button 1 - rotate
Button 2 - pan
Button 3 - uniform scale
ctrl-Button 1 - spin
ctrl-Button 2 - dolly.
Keyboard bindings (upper or lower case):
j - joystick like mouse interactions
t - trackball like mouse interactions
o - object/ actor interaction
c - camera interaction
r - reset camera view
w - turn all actors wireframe
s - turn all actors surface
u - execute user defined function
p - pick actor under mouse pointer (if pickable)
3 - toggle in/out of 3D mode (if supported by renderer)
e - exit
q - exit
2007年11月29日 星期四
2007年11月14日 星期三
Close but no Cigar for Netflix Recommender System
Close but no Cigar for Netflix Recommender System
Posted by CmdrTaco on Wednesday November 14, @10:00AMfrom the fifty-grand-aint-bad dept.
Ponca City, We Love You writes "In October 2006, Netflix, the online movie rental service, announced that it would award $1 million to the first team to improve the accuracy of Netflix's movie recommendations by 10% based on personal preferences. Each contestant was given a set of data from which three million predictions were made about how certain users rated certain movies and Netflix compared that list with the actual ratings and generated a score for each team. More than 27,000 contestants from 161 countries submitted their entries and some got close, but not close enough. Today Netflix announced that it is awarding an annual progress prize of $50,000 to a group of researchers at AT&T Labs, who improved the current recommendation system by 8.43 percent but the $1 million grand prize is still up for grabs and a $50,000 progress prize will be awarded every year until the 10 percent goal is met. As part of the rules of the competition, the team was required to disclose their solution publicly. (pdf)"
Posted by CmdrTaco on Wednesday November 14, @10:00AMfrom the fifty-grand-aint-bad dept.
Ponca City, We Love You writes "In October 2006, Netflix, the online movie rental service, announced that it would award $1 million to the first team to improve the accuracy of Netflix's movie recommendations by 10% based on personal preferences. Each contestant was given a set of data from which three million predictions were made about how certain users rated certain movies and Netflix compared that list with the actual ratings and generated a score for each team. More than 27,000 contestants from 161 countries submitted their entries and some got close, but not close enough. Today Netflix announced that it is awarding an annual progress prize of $50,000 to a group of researchers at AT&T Labs, who improved the current recommendation system by 8.43 percent but the $1 million grand prize is still up for grabs and a $50,000 progress prize will be awarded every year until the 10 percent goal is met. As part of the rules of the competition, the team was required to disclose their solution publicly. (pdf)"
2007年11月10日 星期六
2007年11月2日 星期五
2007年11月1日 星期四
用Cygwin/rsync將Windows的檔案備份到Linux
有啥困難？大家都會，不是嗎？
再仔細想想，中文好像會有問題，對不對？
現在的Linux大部分都用UTF-8來處理中文檔名了吧！
說一下我的解法：
再仔細想想，中文好像會有問題，對不對？
現在的Linux大部分都用UTF-8來處理中文檔名了吧！
說一下我的解法：
- 安裝Cygwin，別忘了把openssh和rsync也順便打勾唷！
- 安裝UTF-8 Cygwin
- 在~/.bashrc加入【alias ls="ls --show-control-chars"】，重進Cygwin Bash Shell
- 先ls看看您的中文檔名正不正常吧！
- 如果可以，rsync應該也可以囉！【rsync -auv /cygdrive/c/Incoming/* 10.0.0.3:Incoming】
- 趕快上你的Linux box看看中文檔名對不對吧！
重點就是UTF-8 Cygwin。對了，不習慣用Cygwin Shell的人，趕快去下載PuTTYcyg，超好用的。不過，別忘了Translation也要改成UTF-8，看中文檔名才OK唷！
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