[B! analytics] gandenã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

ganden id:ganden

analyticsã«é–¢ã™ã‚‹gandenã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (11)

${{author_name}}$

{{{comment_expanded}}}

{{label}}

{{#is_bookmark}}ãƒªã‚¹ãƒˆ{{/is_bookmark}}{{^is_bookmark}}ãƒªãƒ³ã‚¯{{/is_bookmark}}

${{author_name}}$
{{author_name}}{{created}}
{{ #comment }}{{ comment }}{{ /comment }}
- {{ label }}

${{author_name}}$

{{{comment_expanded}}}

{{label}}

{{#is_bookmark}}ãƒªã‚¹ãƒˆ{{/is_bookmark}}{{^is_bookmark}}ãƒªãƒ³ã‚¯{{/is_bookmark}}

æ™‚ç³»åˆ—ãƒ‡ãƒ¼ã‚¿ã¸ã®å›žå¸°åˆ†æž | Logics of Blue
æ–°è¦ä½œæˆï¼š2017å¹´05æœˆ16æ—¥ æœ€çµ‚æ›´æ–°ï¼š2017å¹´05æœˆ16æ—¥ ã“ã“ã§ã¯ã€æ™‚ç³»åˆ—ãƒ‡ãƒ¼ã‚¿ã‚’æ‰‹ã«ã—ãŸéš›ã«ã€ã©ã®ã‚ˆã†ãªæ‰‹é †ã§å›žå¸°åˆ†æžã‚’ã‹ã‘ã¦ã„ã‘ã°ã„ã„ã®ã‹ã€ãƒ•ãƒãƒ¼ãƒãƒ£ãƒ¼ãƒˆã‚’äº¤ãˆã¦è§£èª¬ã—ã¾ã™ã€‚ æ™‚ç³»åˆ—ãƒ‡ãƒ¼ã‚¿ã¯ç‰¹æ®Šã§ã—ã¦ã€æ™®é€šã®å›žå¸°åˆ†æžã‚’è¡Œã†ã¨ã€på€¤ãŒãŠã‹ã—ããªã‚Šã€æ£ã—ãæ¤œå®šãŒã§ããªããªã‚‹ã“ã¨ãŒã‚ˆãã‚ã‚Šã¾ã™ã€‚ã“ã‚Œã‚’è¦‹ã›ã‹ã‘ã®å›žå¸°ã¨å‘¼ã³ã¾ã™ã€‚ ã‚·ãƒŸãƒ¥ãƒ¬ãƒ¼ã‚·ãƒ§ãƒ³ã‚’é€šã—ã¦ã€è¦‹ã›ã‹ã‘ã®å›žå¸°ã¨ã„ã†ç¾è±¡ã‚’ç¢ºèªã—ãŸã†ãˆã§ã€ãã‚Œã‚‰ã«å¯¾å¿œã™ã‚‹æ‰‹æ³•ã¨ã—ã¦ã®å˜ä½æ ¹æ¤œå®šãƒ»å…±å’Œåˆ†æ¤œå®šãƒ»ä¸€èˆ¬åŒ–æœ€å°äºŒä¹—æ³•(GLS)ã®åŸºæœ¬çš„ãªè€ƒãˆæ–¹ã¨Rã§ã®å®Ÿè£…æ–¹æ³•ã«ã¤ã„ã¦èª¬æ˜Žã—ã¾ã™ã€‚ ã‚½ãƒ¼ã‚¹ã‚³ãƒ¼ãƒ‰ã¯ã¾ã¨ã‚ã¦ã“ã¡ã‚‰ã«ç½®ã„ã¦ã‚ã‚Šã¾ã™ã€‚ ã‚¹ãƒãƒ³ã‚µãƒ¼ãƒ‰ãƒªãƒ³ã‚¯ ç›®æ¬¡ æ™‚ç³»åˆ—ãƒ‡ãƒ¼ã‚¿ã¸ã®å›žå¸°åˆ†æžãƒ•ãƒãƒ¼ãƒãƒ£ãƒ¼ãƒˆ å˜ä½æ ¹ã¨è¦‹ã›ã‹ã‘ã®å›žå¸° ãƒ‡ãƒ¼ã‚¿ãƒã‚§ãƒƒã‚¯1ã€€å˜ä½æ ¹æ¤œå®šã¨ADFæ¤œå®š è§£æ±ºç–ï¼‘ã€€å·®åˆ†ç³»åˆ—ã¸ã®å›žå¸°åˆ†æž å·®åˆ†ç³»åˆ—ã¸ã®å›žå¸°åˆ†æžã®å•é¡Œç‚¹ ãƒ‡ãƒ¼ã‚¿ãƒã‚§ãƒƒã‚¯ï¼’ã€€å…±
ganden 2017/05/22
statistics

data_science

analytics

time-series
ãƒªãƒ³ã‚¯
Our quest for robust time series forecasting at scale
by ERIC TASSONE, FARZAN ROHANI We were part of a team of data scientists in Search Infrastructure at Google that took on the task of developing robust and automatic large-scale time series forecasting for our organization. In this post, we recount how we approached the task, describing initial stakeholder needs, the business and engineering contexts in which the challenge arose, and theoretical an
ganden 2017/05/04
google

time-series

analytics

forecast

data_science
ãƒªãƒ³ã‚¯
GitHub - google/CausalImpact: An R package for causal inference in time series
This R package implements an approach to estimating the causal effect of a designed intervention on a time series. For example, how many additional daily clicks were generated by an advertising campaign? Answering a question like this can be difficult when a randomized experiment is not available. The package aims to address this difficulty using a structural Bayesian time-series model to estimate
ganden 2017/05/04
google

time-series

analytics
ãƒªãƒ³ã‚¯
Apache Zeppelin
Apache Zeppelin Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala, Python, R and more.
ganden 2015/10/01
spark

analytics

visualization
ãƒªãƒ³ã‚¯
http://mnutt.github.com/hummingbird/
ganden 2010/07/11
web

analytics
ãƒªãƒ³ã‚¯
ã€Œè†¨å¤§ãªãƒ‡ãƒ¼ã‚¿ã‚’åˆ†æžã—ã¦è¦‹ãˆã¦ãã‚‹ã“ã¨ã€ãƒ‹ã‚³ãƒ‹ã‚³å‹•ç”»ãƒ‡ãƒ¼ã‚¿åˆ†æžç ”ç©¶ç™ºè¡¨ä¼š
æ—¥æœ¬æœ€å¤§ã®å‹•ç”»æŠ•ç¨¿ã‚µãƒ¼ãƒ“ã‚¹ã€Œãƒ‹ã‚³ãƒ‹ã‚³å‹•ç”»ã€ã¯ã€å‹•ç”»ä¸Šã‚’æµã‚Œã‚‹ã‚³ãƒ¡ãƒ³ãƒˆã‚„ã€è‡ªç”±ã«ç·¨é›†ã§ãã‚‹ã‚¿ã‚°æ©Ÿèƒ½ã¨ã„ã£ãŸç‰¹å¾´ã‚’æŒã¡ã€å˜ãªã‚‹å‹•ç”»å…±æœ‰ã‚µãƒ¼ãƒ“ã‚¹ã«ã¨ã©ã¾ã‚‰ãšã€ã‚³ãƒŸãƒ¥ãƒ‹ãƒ†ã‚£ã‚µã‚¤ãƒˆã¨ã—ã¦ã®å´é¢ã‚‚æŒã¤ã€‚å¤šãã®äººãŒã‚¢ã‚¯ã‚»ã‚¹ã™ã‚‹ä¸ã§ã€Œã‚¢ã‚¤ãƒ‰ãƒ«ãƒžã‚¹ã‚¿ãƒ¼ã€ã€ŒåˆéŸ³ãƒŸã‚¯ï¼ˆVOCALOIDï¼‰ã€ã€Œæ±æ–¹ãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã€ãªã©ã€ã„ã‚ã„ã‚ãªãƒ ãƒ¼ãƒ–ãƒ¡ãƒ³ãƒˆãŒç”Ÿã¾ã‚Œã¦ããŸã€‚ ä»Šã‚‚æ¯Žæ—¥å¤šãã®å‹•ç”»ãŒæŠ•ç¨¿ã•ã‚Œã¦ãŠã‚Šã€å„å‹•ç”»ã¯ã€Œå†ç”Ÿæ•°ã€ã€Œã‚³ãƒ¡ãƒ³ãƒˆæ•°ã€ã€Œãƒžã‚¤ãƒªã‚¹ãƒˆæ•°ã€ãªã©ã®æƒ…å ±ãŒã‚ã‹ã‚‹ã‚ˆã†ã«ãªã£ã¦ã„ã‚‹ã€‚ã™ã§ã«æŠ•ç¨¿å‹•ç”»æ•°ã¯200ä¸‡æœ¬ã‚’è¶…ãˆã‚‹ãŒã€ã“ã‚Œã‚‰è†¨å¤§ãªãƒ‡ãƒ¼ã‚¿ã‚’åˆ†æžã™ã‚‹ã“ã¨ã§ã€ã©ã‚“ãªç¾è±¡ã‚„ã‚³ãƒŸãƒ¥ãƒ‹ã‚±ãƒ¼ã‚·ãƒ§ãƒ³ãŒèµ·ãã¦ã„ã‚‹ã®ã‹ã‚’æ˜Žã‚‰ã‹ã«ã—ã‚ˆã†ã¨ã™ã‚‹ã®ãŒä»Šå›žã®ç™ºè¡¨ä¼šã®ç›®çš„ã§ã‚ã‚‹ã€‚ åˆ†æžã™ã‚‹éš›ã®2ã¤ã®éšœå£ ç‹¬è‡ªã«ãƒ‡ãƒ¼ã‚¿åŽé›†ãŒå¿…è¦ã§ã‚ã‚‹ã“ã¨ ã—ã‹ã—ã€ãã‚‚ãã‚‚ãƒ‹ã‚³ãƒ‹ã‚³å‹•ç”»è‡ªä½“ã¯ãƒ‡ãƒ¼ã‚¿ã‚’åˆ†æžã—ã‚„ã™ã„ã‚ˆã†ã«åºƒãæä¾›ã—ã¦ã„ã‚‹ã‚ã‘ã§ã¯ãªã„ã€‚1ã¤1ã¤ã®å‹•ç”»ã®å†ç”Ÿæ•°
ganden 2009/01/27
niconico

analytics

network

visualization

research

community
ãƒªãƒ³ã‚¯
ã¯ã¦ãƒ–ãƒ¦ãƒ¼ã‚¶é–“ã®é¡žä¼¼åº¦ - Life like a clown
æ³¨ç›®ã®å‹•ç”»å•é¡Œã¨ç·åˆãƒ¡ãƒ‡ã‚£ã‚¢è«–äº‹ä»¶ã¨ã®é–¢é€£ ã„ã¤ã‹æ›¸ã“ã†ã¨æ€ã„ã¤ã¤éšåˆ†ã¨æ”¾ç½®ã—ã¦ã„ãŸè©±é¡Œï¼Žãã£ã‹ã‘ã¯ï¼ŒNO!ã¨è¨€ãˆã‚‹ã‚ˆã†ã«ãªã‚ŠãŸã„ï¼šã€Œæ³¨ç›®ã®å‹•ç”»ã€ã¯æœ¬å½“ã«åŠ£åŒ–ã—ãŸã®ã‹ã‚ˆã‚Šï¼Žæ³¨ç›®ã®å‹•ç”»ï¼ˆç‰¹ã«ãƒ‹ã‚³ãƒ‹ã‚³å‹•ç”»å´ï¼Ÿï¼‰ã«ã‚¢ã‚¤ãƒ‰ãƒ«ãƒžã‚¹ã‚¿ãƒ¼ã‚„ã‚‰ã‚¢ãƒ‹ãƒ¡é–¢ä¿‚ã®å‹•ç”»ã°ã‹ã‚ŠãŒæŒ™ãŒã£ã¦ã„ã¦[ã“ã‚Œã¯ã²ã©ã„]ã¨è¨€ã†è©±é¡ŒãŒä¸€æ™‚æœŸç››ã‚“ã§ã—ãŸï¼Žã“ã‚Œã«é–¢é€£ã—ã¦ï¼Œã²ã¨ã¤æ°—ã«ãªã£ã¦ã„ãŸã“ã¨ãŒã‚ã£ãŸã®ã§èª¿ã¹ã¦ã¿ã¾ã—ãŸï¼Ž æ³¨ç›®ã®å‹•ç”»ï¼ˆãƒ‹ã‚³ãƒ‹ã‚³å‹•ç”»ï¼‰ã‹ã‚‰idolm@sterã‚¿ã‚°ã®ã¤ã„ã¦ã„ã‚‹ã‚¨ãƒ³ãƒˆãƒªã‚’æ–°ã—ã„ã‚‚ã®ã‹ã‚‰50å€‹æŠœãå‡ºã—ã¦ï¼Œãã‚Œã‚‰ã®ã‚¨ãƒ³ãƒˆãƒªã‚’ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ã—ã¦ã„ã‚‹ãƒ¦ãƒ¼ã‚¶ã®åˆ†å¸ƒã‚’èª¿ã¹ã¾ã—ãŸï¼Žãã®çµæžœãŒã“ã¡ã‚‰ï¼ˆå®Œå…¨ãªãƒã‚°ï¼šuser_dist_nicovideo.logï¼‰ï¼Žä¸€ç•ªå³ãŒãƒ¦ãƒ¼ã‚¶åã§ï¼Œãã®éš£ãŒ50ã‚¨ãƒ³ãƒˆãƒªã®ä¸ã§ãã®ãƒ¦ãƒ¼ã‚¶ãŒãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ã—ã¦ã„ãŸã‚¨ãƒ³ãƒˆãƒªã®æ•°ã§ã™ï¼Ž get 50 entries 0 47 Ubuntu 1 44 ak9
ganden 2008/08/21
hatena

bookmark

analytics
ãƒªãƒ³ã‚¯
makuchan's diary
â–²ã©ã“ã‹ã‚‰ã¿ã¦ã‚‚ã‚¹ãƒ¼ãƒ‘ãƒ¼ãƒžãƒ³ã˜ã‚ƒãªã„ã€‚ã€€#å‹•ç‰©ã¯ã‚ãªãŸã®ã”ã¯ã‚“ã˜ã‚ƒãªã„ ã‚†ã‹ã‚Šå§«ã€‚ä»Šæœˆã§38æ³ã‹ã€‚ QX10ãŒå±Šã„ãŸã®ã§è»½ãæ’®å½±ã—ã¦ã¿ãŸã€‚ ã¾ãšãƒ¡ãƒ¢ãƒªãƒ¼ã‚«ãƒ¼ãƒ‰ãŒå¿…è¦ã ï¼ï½— ã¾ãç„¡ãã¦ã‚‚ã‚¹ãƒžãƒ›ã«è‡ªå‹•è»¢é€ã—ã¦ãã‚Œã‚‹ã‘ã©ã€‚iPhone5ã®è»½ã•ã«ã“ã®ãƒ¬ãƒ³ã‚ºã®é‡ã•ã¯ãƒãƒ©ãƒ³ã‚¹æ‚ªã„ã€‚æ…£ã‚ŒãŒå¿…è¦ã‹ã‚‚ã€‚ è‚å¿ƒã®ç”»è³ªã ã‘ã©ã€å®¤å†…æ’®å½±ã§è¦‹ã¦ã¿ã‚‹ã¨æ™®é€šã®ã‚³ãƒ³ãƒ‡ã‚¸ãƒ¬ãƒ™ãƒ«ã§å‡„ã•ã‚’æ„Ÿã˜ãªã„ã€‚ ã‚ã¨wifiæŽ¥ç¶šã«æ™‚é–“ãŒã‹ã‹ã‚‹ã€‚ã‚µãƒƒã¨å‡ºã—ã¦æ’®å½±ã¨ã„ã†ã‚ã‘ã«ã¯ã„ã‹ãªã„ã‚ˆã†ã ã€‚ ã¬ãƒ¼ã‚“ã€‚å¾®å¦™ã€‚ ãã‚“ã©ã‚ã„ã© é›ªãƒŸã‚¯ Magical Snow Ver.ã®å¼•æ›åˆ¸ã‚’å—ã‘å–ã£ã¦ããŸã€‚ ã‚ã¨ã¯å½“æ—¥ã‚µãƒƒãƒãƒãƒ•ã‚¡ã‚¯ãƒˆãƒªãƒ¼ã«è¡Œãã ã‘ã ï¼ï¼ˆï¾Ÿâˆ€ï¾Ÿï¼‰
ganden 2008/02/29
3d

game

analytics
ãƒªãƒ³ã‚¯
ã€æœ¬éŸ³ã€‘ã‚¹ãƒˆãƒ©ãƒƒã‚·ãƒ¥ç¦å²¡å¤©ç¥žåº—ã®å£ã‚³ãƒŸ7é¸ï¼†ã‚¢ãƒ©ã‚µãƒ¼å¥³åã®æœ¬éŸ³10é¸
æ›´æ–°ï¼š2022/2/24 ã€æœ¬éŸ³ã€‘ã‚¹ãƒˆãƒ©ãƒƒã‚·ãƒ¥ç¦å²¡å¤©ç¥žåº—ã®å£ã‚³ãƒŸ7é¸ï¼†ã‚¢ãƒ©ã‚µãƒ¼å¥³åã®æœ¬éŸ³10é¸ï¼š2022å¹´2æœˆ24æ—¥æ›´æ–°æ¸ˆ ãƒãƒƒãƒˆæ¤œç´¢ã§å‡ºã¦ããŸã‚¹ãƒˆãƒ©ãƒƒã‚·ãƒ¥ã®ç¦å²¡å¤©ç¥žåº—ãŒã‚ã£ã¡ã‚ƒæ°—ã«ãªã‚‹ãªãã€‚ è„±æ¯›ã‚µãƒãƒ³ã¨ã—ã¦è‰¯ã•ãã†ã ã‘ã©ã€ã»ã‚“ã¨ã«ç—›ããªã„ã®ã‹ãªï¼Ÿ é€šã£ã¦ã„ã‚‹äººã®å£ã‚³ãƒŸã‚’ã¿ã¦ã¿ãŸã„ãªããƒ¼ã€‚ ãªã‚“ã¦ãµã¨æ°—ã«ãªã£ãŸã®ã§ã€ã•ã£ããã‚¹ãƒˆãƒ©ãƒƒã‚·ãƒ¥ã®å£ã‚³ãƒŸã‚„æ–™é‡‘ãƒ—ãƒ©ãƒ³ã€ãŠå¾—ãªã‚ãƒ£ãƒ³ãƒšãƒ¼ãƒ³ã«ã¤ã„ã¦èª¿ã¹ã¦ã¿ã¾ã—ãŸï¼ï¼ ã‚¹ãƒˆãƒ©ãƒƒã‚·ãƒ¥ã®ç¦å²¡å¤©ç¥žåº—ã®ç„¡æ–™ã‚«ã‚¦ãƒ³ã‚»ãƒªãƒ³ã‚°ã‚’äºˆç´„ã—ã¡ã‚ƒã†å‰ã«å¿…ãšãƒã‚§ãƒƒã‚¯ã—ã¦ä¸‹ã•ã„ããƒ¼ã€‚ ã¡ãªã¿ã«ã€ã‚¹ãƒˆãƒ©ãƒƒã‚·ãƒ¥ã¨ä¼¼ãŸã‚ˆã†ãªè„±æ¯›ã‚µãƒãƒ³åº—ãŒã‚ã‚‹ã‹ã‚‚çŸ¥ã‚Œãªã„ã§ã™ãŒã€ä»Šå›žèª¿ã¹ã¦ã¿ãŸã®ã¯ã€ã“ã¡ã‚‰ã®ã‚¹ãƒˆãƒ©ãƒƒã‚·ãƒ¥(STLASSH)ã®ãŠåº—ã§ã™ã€‚
ganden 2007/12/02
niconico

ranking

analytics
ãƒªãƒ³ã‚¯
MarkeZineï¼šâ—ŽJavaScriptã‚’åˆ©ç”¨ã—ã¦Google Analyticsã‚’è³¢ãæ´»ç”¨ã™ã‚‹
ã€ŽMarkeZineã€ãŒä¸»å‚¬ã™ã‚‹ãƒžãƒ¼ã‚±ãƒ†ã‚£ãƒ³ã‚°ãƒ»ã‚¤ãƒ™ãƒ³ãƒˆã€ŽMarkeZine Dayã€ã€ŽMarkeZine Academyã€ã€ŽMarkeZine ãƒ—ãƒ¬ãƒŸã‚¢ãƒ ã‚»ãƒŸãƒŠãƒ¼ã€ã® æœ€æ–°æƒ…å ±ã‚’ã¯ã˜ã‚ã€æ§˜ã€…ãªã‚¤ãƒ™ãƒ³ãƒˆæƒ…å ±ã‚’ã¾ã¨ã‚ã¦ã”ç´¹ä»‹ã—ã¾ã™ã€‚ MarkeZine Day
ganden 2007/10/27
analytics

google

javascript
ãƒªãƒ³ã‚¯
ã‚¦ã‚§ãƒ–ã‚µã‚¤ãƒˆã®ãƒˆãƒ©ãƒ•ã‚£ãƒƒã‚¯ã‚’åˆ†æžã™ã‚‹50ã®æ–¹æ³• - ãƒã‚¿ãƒ•ãƒ«
Analytics Toolbox: 50+ Ways to Track Website Trafficã¨ã„ã†ã‚¨ãƒ³ãƒˆãƒªãƒ¼ã‚ˆã‚Šã€‚ From analyzing your RSS feed to counting page views to visual representations of where your visitors are clicking, there is no shortage of companies looking to help you better understand your web siteâ€™s traffic. ã‚¦ã‚§ãƒ–ã‚µã‚¤ãƒˆã®ãƒˆãƒ©ãƒ•ã‚£ãƒƒã‚¯ã‚’åˆ†æžã™ã‚‹ãŸã‚ã®ã€50ã®æ–¹æ³•ãŒç´¹ä»‹ã•ã‚Œã¦ã„ã‚‹ã‚¨ãƒ³ãƒˆãƒªãƒ¼ã§ã™ã€‚ ä¸€å£ã§è¨€ã†ã¨ã€ã‚¢ã‚¯ã‚»ã‚¹è§£æžã¨ã„ã†ã“ã¨ã«ãªã‚‹ã®ã ã¨æ€ã„ã¾ã™ãŒã€æ§˜ã€…ãªã‚µã‚¤ãƒˆãŒã‚ã‚‹ã®ã§ã™ãã€‚ ã‚«ãƒ†ã‚´ãƒªãƒ¼ã¨ã—ã¦ã¯ã€ ãƒ»Web Traffic Visualizati
ganden 2007/06/28
web

analytics
ãƒªãƒ³ã‚¯
1