[B! learning] AkihitoKã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

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learningã«é–¢ã™ã‚‹AkihitoKã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (44)

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ã“ã®é€£è¼‰ã§ã¯ã€æ©Ÿæ¢°å¦ç¿’ã«ã¾ã ãªã˜ã¿ãŒãªã„ITãƒžãƒã‚¸ãƒ£ãƒ¼ã‚„ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã«å‘ã‘ã¦ã€ãƒ“ã‚¸ãƒã‚¹ã¸ã®æ´»ç”¨ã‚’å‰æã«ã€æ©Ÿæ¢°å¦ç¿’ã¨ãã®å¿œç”¨ã«ã¤ã„ã¦èª¬æ˜Žã—ã¦ã„ã‚‹ã€‚å‰å›žï¼ˆæ©Ÿæ¢°å¦ç¿’ã§æ€–ã„ã€Œæ¬¡å…ƒã®å‘ªã„ã€ã€æ‰‹æ³•ã®é¸æŠžã¯é©æé©æ‰€ã§ï¼‰ã¯ã€æ©Ÿæ¢°å¦ç¿’ã‚’å¿œç”¨ã™ã‚‹éš›ã«æŠ¼ã•ãˆã¦ãŠããŸã„å‹˜æ‰€ã‚’ç´¹ä»‹ã—ãŸã€‚ ä»Šå›žã¯æ©Ÿæ¢°å¦ç¿’ã®å…·ä½“çš„ãªå¿œç”¨ä¾‹ã¨ã—ã¦ã€Œã‚»ãƒ³ã‚µãƒ¼è¡Œå‹•èªè˜ã€ã‚’å–ã‚Šä¸Šã’ã‚‹ã€‚ç†è€…ãŒæ‰‹æŽ›ã‘ãŸãƒ˜ãƒ«ã‚¹ã‚±ã‚¢åˆ†é‡Žã¸ã®äº‹ä¾‹ã‚’é¡Œæã«ã—ã¦ã€èª¬æ˜Žã—ãŸã„ã€‚ ã‚»ãƒ³ã‚µãƒ¼ã‹ã‚‰å¾—ãŸãƒ‡ãƒ¼ã‚¿ã‚’åŸºã«äººé–“ã®è¡Œå‹•ã‚’èªè˜ IoTï¼ˆInternet of Thingsï¼‰ã¯ã€ã„ã¾æœ€ã‚‚æ³¨ç›®ã‚’é›†ã‚ã¦ã„ã‚‹ITåˆ†é‡Žã®ä¸€ã¤ã ã€‚ãã®èƒŒæ™¯ã¨ã—ã¦ã€ã‚»ãƒ³ã‚µãƒ¼ãŒèº«è¿‘ãªå˜åœ¨ã«ãªã£ãŸã“ã¨ãŒæŒ™ã’ã‚‰ã‚Œã‚‹ã€‚ ä¾‹ãˆã°ã‚¹ãƒžãƒ¼ãƒˆãƒ•ã‚©ãƒ³ã®å¤šãã¯ã€ãƒãƒã®å¤‰åŒ–ã‚’æ¸¬ã‚‹ä¸‰è»¸åŠ é€Ÿåº¦ã‚»ãƒ³ã‚µãƒ¼ã‚„ã€æŒ¯å‹•ã™ã‚‹ç‰©ä½“ãŒå›žè»¢ã™ã‚‹ã¨ãã«ã‹ã‹ã‚‹åŠ›ï¼ˆã‚³ãƒªã‚ªãƒªåŠ›ï¼‰ã‚’æ¸¬ã‚‹è§’é€Ÿåº¦ã‚»ãƒ³ã‚µãƒ¼ï¼ˆã‚¸ãƒ£ã‚¤ãƒã‚»ãƒ³ã‚µãƒ¼ã¨ã‚‚ã„ã†ï¼‰ãªã©ã‚’æè¼‰ã—ã¦ã„ã‚‹ã€‚åŠå°Žä½“é›†ç©æŠ€è¡“ã‚’
AkihitoK 2016/08/25
IOT

machine

learning
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ITæ´»ç”¨ã§é›»åŠ›å°å£²äº‹æ¥ã‚’æ”¯æ´ã™ã‚‹ã‚ªãƒ—ãƒ†ã‚£ãƒžã‚¤ã‚¶ãƒ¼ï¼ˆæ±äº¬éƒ½æ¸¯åŒºï¼‰ã¯8æœˆ4æ—¥ã€åŒç¤¾ã®ææ¡ˆã™ã‚‹ã€Œå†ç”Ÿå¯èƒ½ã‚¨ãƒãƒ«ã‚®ãƒ¼ç™ºé›»å¯¾å¿œã®äººå·¥çŸ¥èƒ½ã«ã‚ˆã‚‹ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ å…¥æœè‡ªå‹•åŒ–æŠ€è¡“ã®é–‹ç™ºã€ãŒã€NEDOï¼ˆæ–°ã‚¨ãƒãƒ«ã‚®ãƒ¼ãƒ»ç”£æ¥æŠ€è¡“ç·åˆé–‹ç™ºæ©Ÿæ§‹ï¼‰ã®ã€Œå¹³æˆ28å¹´åº¦æ–°ã‚¨ãƒãƒ«ã‚®ãƒ¼ãƒ™ãƒ³ãƒãƒ£ãƒ¼æŠ€è¡“é©æ–°äº‹æ¥ã€ã«æŽ¡æŠžã•ã‚ŒãŸã¨ç™ºè¡¨ã—ãŸã€‚ äººå·¥çŸ¥èƒ½ã«ã‚ˆã‚‹æ©Ÿæ¢°å¦ç¿’ã‚’å¿œç”¨ã—ã€å¤ªé™½å…‰ãªã©ã®å†ã‚¨ãƒç™ºé›»é‡ã‚’é«˜ã„ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ æ€§ã§äºˆæ¸¬ã™ã‚‹æŠ€è¡“ã‚’é–‹ç™ºã™ã‚‹ã€‚å°å£²é›»æ°—äº‹æ¥è€…ã¨ç™ºé›»äº‹æ¥è€…ã€éœ€è¦å®¶ã‚’ã¤ãªãŽã¤ã¤ã€å†ã‚¨ãƒåˆ©ç”¨ã®å‰²åˆã‚’é«˜ã‚ã¦ã‚‚ã€ä½™è£•ã‚’ã‚‚ã£ãŸé›»åŠ›å–å¼•ã®å®Ÿç¾ã‚’ç›®æŒ‡ã™ã¨ã„ã†ã€‚ ã‚ªãƒ—ãƒ†ã‚£ãƒžã‚¤ã‚¶ãƒ¼ã¯ã€WEBãƒžãƒ¼ã‚±ãƒ†ã‚£ãƒ³ã‚°ã®é ˜åŸŸã§æ—©ãã‹ã‚‰æ©Ÿæ¢°å¦ç¿’ã«ã‚ˆã‚‹äººå·¥çŸ¥èƒ½åž‹ã®äºˆæ¸¬æŠ€è¡“ã‚’ç ”ç©¶ã—ã€å®Ÿéš›ã«æ´»ç”¨ã—ã¦ã„ã‚‹ã¨ã„ã†ã€‚ãã®æŠ€è¡“ã‚’å¿œç”¨ã—ã€é›»åŠ›æµé€šã‚’çµ±åˆç®¡ç†ã§ãã‚‹æ¬¡ä¸–ä»£åž‹ã€Œã‚¨ãƒãƒ«ã‚®ãƒ¼ç®¡ç†ã‚µãƒ¼ãƒ“ã‚¹ã€ã‚’æ§‹ç¯‰ã™ã‚‹ã€‚ åŒã‚µãƒ¼ãƒ“ã‚¹ã®å®Ÿç¾ã«ã¯ã€é›»åŠ›éœ€è¦ã¨å†ã‚¨ãƒç™ºé›»ã®äºˆæ¸¬æŠ€è¡“ã®é«˜ç²¾åº¦åŒ–ãŒåŸºç›¤
AkihitoK 2016/08/16
machine

learning
ãƒªãƒ³ã‚¯
The current state of machine intelligence 2.0
Autonomous systems and focused startups among major changes seen in past year. Cartographical representation of a self-organizing map based on Wikipedia featured article data. Distance is inversely proportional to similarity. The "mountains" are edges between clusters.. (source: By Denoir on Wikimedia Commons) A year ago today, I published my original attempt at mapping the machine intelligence ec
AkihitoK 2015/12/14
machine

learning
ãƒªãƒ³ã‚¯
Where are the opportunities for machine learning startups? [guest post]
AkihitoK 2015/12/11
machine

learning
ãƒªãƒ³ã‚¯
Two examples of why machine learning is becoming the most powerful way to increase revenue â€” Medium
AkihitoK 2015/07/24
algo

machine

learning
ãƒªãƒ³ã‚¯
Airbnb is using machine learning to help hosts make as much money as possible
AkihitoK 2015/06/05
machine

learning
ãƒªãƒ³ã‚¯
Machine Learning Goes Mainstream II: Guesswork Automates CRM With Digital Division Of Labor
Machine learning is a term you can expect to hear a lot in coming years. ML makes no claims to sentience or general intelligence, but it can be very useful if you have large and fairly consistent sets of data. But what if you are a small company without a lot of data? Or perhaps a large company with a new product line and no relevant sales data from existing customers? Not having enough data to cr
AkihitoK 2015/05/29
machine

learning
ãƒªãƒ³ã‚¯
'Deep Learning' Will Soon Give Us Super-Smart Robots
AkihitoK 2015/05/28
deep

learning

robot
ãƒªãƒ³ã‚¯
ãƒ¯ãƒ³ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã‚’å¼·ã¿ã«ã™ã‚‹SaaSåž‹ERPã®ãƒ¯ãƒ¼ã‚¯ãƒ‡ã‚¤--æ©Ÿæ¢°å¦ç¿’ã§é›¢è·ãƒªã‚¹ã‚¯æ¸¬å®š
å°åˆ·ã™ã‚‹ ãƒ¡ãƒ¼ãƒ«ã§é€ã‚‹ ãƒ†ã‚ã‚¹ãƒˆ HTML é›»åæ›¸ç± PDF ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰ ãƒ†ã‚ã‚¹ãƒˆ é›»åæ›¸ç± PDF ã‚¯ãƒªãƒƒãƒ—ã—ãŸè¨˜äº‹ã‚’Myãƒšãƒ¼ã‚¸ã‹ã‚‰èªã‚€ã“ã¨ãŒã§ãã¾ã™ SaaSå½¢å¼ã§äººäº‹ã‚„è²¡å‹™ãªã©ã®åŸºå¹¹æ¥å‹™ã‚·ã‚¹ãƒ†ãƒ ï¼ˆERPï¼‰ã‚’æä¾›ã™ã‚‹Workdayã®æ—¥æœ¬æ³•äººã¯5æœˆ26æ—¥ã€æ—¥æœ¬ã§ã®äº‹æ¥çŠ¶æ³ã‚’èª¬æ˜Žã™ã‚‹è¨˜è€…å‘ã‘ãƒ–ãƒªãƒ¼ãƒ•ã‚£ãƒ³ã‚°ã‚’é–‹å‚¬ã—ãŸã€‚æ©Ÿæ¢°å¦ç¿’ã‚’æ´»ç”¨ã—ãŸäººäº‹ã‚·ã‚¹ãƒ†ãƒ ã®æ–°æ©Ÿèƒ½ã‚‚ç´¹ä»‹ã—ã¦ã„ã‚‹ã€‚ ã¾ãŸã€ç±³å›½ã§ã¯åŒæ—¥ã«ã€æ—¥æœ¬ã®å¤§æ‰‹è£½é€ æ¥ãŒæ–°ãŸã«åŒç¤¾ã®ã‚µãƒ¼ãƒ“ã‚¹ã‚’æŽ¡ç”¨ã™ã‚‹ã“ã¨ã‚’ç™ºè¡¨ã™ã‚‹äºˆå®šã¨ã®ã“ã¨ã€‚ æ—¥æœ¬æ³•äººã®ä»£è¡¨å–ç· å½¹ç¤¾é•·ã‚’å‹™ã‚ã‚‹é‡‘ç¿°æ–°æ°ã¯ã€å›½å†…ã§ã®ãƒ•ã‚¡ãƒ¼ã‚¹ãƒˆãƒªãƒ†ã‚¤ãƒªãƒ³ã‚°ã«ã‚ˆã‚‹æŽ¡ç”¨ã‚’ãã£ã‹ã‘ã«ã€å•†è«‡ã®é€²ã¿å…·åˆãŒé£›èºçš„ã«è‰¯ããªã£ã¦ãã¦ã„ã‚‹ã¨è©±ã—ãŸã€‚æ—¥æœ¬ã§çµ¦ä¸Žè¨ˆç®—ã‚¢ã‚¦ãƒˆã‚½ãƒ¼ã‚·ãƒ³ã‚°äº‹æ¥ã‚’æ‰‹æŽ›ã‘ã‚‹ãƒšã‚¤ãƒãƒ¼ãƒ«ã¨5æœˆ12æ—¥ã«ã€ãƒ‘ãƒ¼ãƒˆãƒŠãƒ¼ã‚·ãƒƒãƒ—ã‚’ç· çµã—ãŸã“ã¨ã«ã‚‚è§¦ã‚ŒãŸã€‚ é‡‘æ°ã¯ã€Workdayã®å¼·ã¿ã«ã¤ã„ã¦ã€Œãƒ¦ãƒ¼ã‚¶ãƒ¼ä¼æ¥å…¨925ç¤¾
AkihitoK 2015/05/26
machine

learning

work
ãƒªãƒ³ã‚¯
Machine learning can predict emerging infectious diseases
AkihitoK 2015/05/21
machine

learning
ãƒªãƒ³ã‚¯
How Machine Learning Is Eating the Software World
Follow BigDATAwire: [wpsr_follow_icons facebook=â€https://www.facebook.com/BigDATAwire/â€ twitter=â€https://www.twitter.com/datanamiâ€ linkedin=â€https://www.linkedin.com/company/datanami/â€ rss=â€https://www.bigdatawire.com/feed/â€ bg_color=â€#1b5e5câ€ shape=â€squircleâ€] Marc Andreessen famously said in 2011 that software was eating the world. Four years later, that trend has accelerated, only now it appear
AkihitoK 2015/05/19
deep

learning
ãƒªãƒ³ã‚¯
Object recognition for free
Caption: The first layers (1 and 2) of a neural network trained to classify scenes seem to be tuned to geometric patterns of increasing complexity, but the higher layers (3 and 4) appear to be picking out particular classes of objects. *Terms of Use: Images for download on the MIT News office website are made available to non-commercial entities, press and the general public under a Creative Commo
AkihitoK 2015/05/11
deep

learning
ãƒªãƒ³ã‚¯
Andrew Ng: Why â€˜Deep Learningâ€™ Is a Mandate for Humans, Not Just Machines
#maketechhuman If venture capital and research funding are any indication, artificial intelligence will play a leading role in shaping our future. And few tech innovators in the private or public sector have been as prominent in defining that role as Andrew Ng, chief scientist at Chinaâ€™s search giant Baidu. Ng has taught AI at Stanford, led the Google Brain project, founded online education pionee
AkihitoK 2015/05/06
deep

learning
ãƒªãƒ³ã‚¯
https://jp.techcrunch.com/2015/05/02/20150501deep-learning-image-analysis-startup-descartes-labs-raises-3-3m-after-spinning-out-of-los-alamos-national-labs/
AkihitoK 2015/05/05
idea

agri

deep

learning
ãƒªãƒ³ã‚¯
https://jp.techcrunch.com/2015/04/10/20150409aws-wants-to-put-machine-learning-in-reach-of-any-developer/
AkihitoK 2015/04/11
machine

learning
ãƒªãƒ³ã‚¯
Machine Learning Algorithm Mines 16 Billion E-Mails
Human e-mailing behavior is so predictable that computer scientists have created an algorithm that can calculate when an e-mail thread is about to end. Electronic mail plays a hugely important role in the lives of a large fraction of the worldâ€™s population. And yet, strangely, little is known about the way people use e-mail. How many e-mail conversations do people have? How long are these conversa
AkihitoK 2015/04/10
machine

learning
ãƒªãƒ³ã‚¯
Amazon Introduce Machine Learning. As A Service
AkihitoK 2015/04/10
machine

learning
ãƒªãƒ³ã‚¯
GTC 2015 - Deep Learningã‚’ç†è§£ã™ã‚‹(å¾Œç·¨)
ãƒ»GTC 2015 - Deep Learningã‚’ç†è§£ã™ã‚‹(å‰ç·¨)ã¯ã‚³ãƒãƒ© ãƒ»GTC 2015 - Deep Learningã‚’ç†è§£ã™ã‚‹(ä¸ç·¨)ã¯ã‚³ãƒãƒ© å¤šãã®å¯¾è±¡ç‰©ãŒå«ã¾ã‚Œã¦ã„ã‚‹ç”»åƒã®èªè˜ã¯é›£ã—ã„ã®ã§ã‚ã‚‹ãŒã€æ¬¡ã®ä¾‹ã®ã‚ˆã†ãªå†™çœŸã§ã¯é£Ÿã¹ç‰©ãŒç¢ºåº¦16%ã§ç¬¬1å€™è£œã€å¤•é£ŸãŒ3.1%ã€ãƒãƒ¼ãƒ™ã‚ãƒ¥ãƒ¼ãŒ2.9%ãƒžãƒ¼ã‚±ãƒƒãƒˆãŒ2.5%ã€é£Ÿäº‹ã¨ä¸ƒé¢é³¥ãŒ1.4%ã§ãªã‹ãªã‹è‰¯ã„èªè˜ãŒä¸¦ã‚“ã§ã„ã‚‹ã€‚å…ƒã®ç”»åƒã¯247KBã§å‡¦ç†æ™‚é–“ã¯110msã§ã‚ã‚‹ã€‚
AkihitoK 2015/04/10
deep

learning
ãƒªãƒ³ã‚¯
GTC 2015 - Deep Learningã‚’ç†è§£ã™ã‚‹(ä¸ç·¨)
(GTC 2015 - Deep Learningã‚’ç†è§£ã™ã‚‹(å‰ç·¨)ã¯ã‚³ãƒãƒ©) å½“åˆã¯å¦ç¿’ã«ä½¿ãˆã‚‹ç”»åƒãŒå°‘ãªã‹ã£ãŸãŒã€ã‚¹ã‚¿ãƒ³ãƒ•ã‚©ãƒ¼ãƒ‰å¤§ãŒImageNetã‚’ç«‹ã¡ä¸Šã’ã€ç¾åœ¨ã§ã¯2ä¸‡ã‚«ãƒ†ã‚´ãƒªã®ãƒ©ãƒ™ãƒ«ä»˜ã‘ãŒã•ã‚ŒãŸã€1400ä¸‡æžšã®ç”»åƒãŒé›†ã‚ã‚‰ã‚Œã¦ã„ã‚‹ã€‚ ImageNetã§ã¯ã€æ¯Žå¹´ã€ ImageNet Large Scale Visual Recognition Challengeã¨ã„ã†ç”»åƒèªè˜ã®ã‚³ãƒ³ãƒšãŒè¡Œã‚ã‚Œã¦ã„ã‚‹ã€‚æ˜¨å¹´ã®ILSVRC2014ã§ã¯45ä¸‡6567æžšã®ãƒˆãƒ¬ãƒ¼ãƒ‹ãƒ³ã‚°(å¦ç¿’)ç”¨ã®ç”»åƒãŒæä¾›ã•ã‚ŒãŸã€‚ã“ã‚Œã‚‰ã®ç”»åƒã«ã¯200ã‚«ãƒ†ã‚´ãƒªã®ç”»åƒãŒå«ã¾ã‚Œã¦ã„ã‚‹ã€‚ãã—ã¦ã€2ä¸‡121æžšã®ãƒãƒªãƒ‡ãƒ¼ã‚·ãƒ§ãƒ³(ç¢ºèª)ç”¨ç”»åƒãŒæä¾›ã•ã‚Œã¦ãŠã‚Šã€ã“ã‚Œã‚’ä½¿ã£ã¦å¦ç¿’ã—ãŸãƒ¢ãƒ‡ãƒ«ã®æŒ¯èˆžã„ã‚’ç¢ºèªã™ã‚‹ã€‚ ãã—ã¦ã€ãƒ†ã‚¹ãƒˆç”¨ã®4ä¸‡152æžšã®ç”»åƒã‚’èªè˜ã—ã¦ã€ãã®çµæžœã‚’ç«¶ã†ã€‚ç«¶ã†ã¨ã„ã£ã¦ã‚‚ä¸€å ‚ã«ä¼šã—ã¦è¡Œã†ã‚ã‘ã§ã¯ãªãã€æœŸé™ã¾ã§ã«æå‡ºã•ã‚ŒãŸèªè˜
AkihitoK 2015/04/10
deep

learning
ãƒªãƒ³ã‚¯
GTC 2015 - Deep Learningä¸€è‰²ã¨ãªã£ãŸåŸºèª¿è¬›æ¼”
NVIDIAãŒä¸»å‚¬ã™ã‚‹ã€ŒGPU Techno logy Conference(GTC)ã€ã¯ã€æ˜¨å¹´ã¨åŒã˜San Jose McEnery Convention Centerã§é–‹å‚¬ã•ã‚ŒãŸã€‚1400ãƒ‰ãƒ«ã¨ã„ã†é«˜é¡ã®å‚åŠ è²»ã«ã‚‚ã‹ã‹ã‚ã‚‰ãš4000äººä»¥ä¸ŠãŒå‚åŠ ã™ã‚‹ã¨ã„ã†äººæ°—ã®ã‚ã‚‹å¦ä¼šã§ã‚ã‚‹ã€‚æ˜¨å¹´ã¨åŒã˜ä¼šå ´ã§ã‚ã‚‹ãŒã€äººæ°—ã‚»ãƒƒã‚·ãƒ§ãƒ³ã¯äººãŒé›†ã¾ã‚Šã™ãŽã¦æ—©ãè¡Œã‹ãªã„ã¨ã€æº€å“¡ã§ç™ºè¡¨ä¼šå ´ã«å…¥ã‚Œãªã„ã¨ã„ã†äº‹æ…‹ãŒå¹¾ã¤ã‚‚èµ·ã“ã£ã¦ãŠã‚Šã€æ˜¨å¹´ã‚ˆã‚Šå‚åŠ è€…ãŒå¢—ãˆã¦ã„ã‚‹æ„Ÿã˜ã§ã‚ã‚‹ã€‚ Jen-Hsun Huang CEOã®åŸºèª¿è¬›æ¼”ã§å¹•ã‚’é–‹ã‘ãŸä»Šå¹´ã®GTCã¯ã€Deep Learningä¸€è‰²ã§ã‚ã£ãŸã€‚Deep Learningã¯å¤šå±¤ã®ãƒ‹ãƒ¥ãƒ¼ãƒ©ãƒ«ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã‚’å¦ç¿’ã•ã›ã€ç”»åƒã€ã‚¹ãƒ”ãƒ¼ãƒã€ãƒ†ã‚ã‚¹ãƒˆãªã©ãŒèªè˜ã§ãã‚‹ã‚ˆã†ã«ã™ã‚‹æŠ€è¡“ã‚’æ„å‘³ã™ã‚‹ã€‚ Jen-Hsun Huang CEOã¯ã€ä»Šå›žã®GTCã§ã®ä¸»è¦ãªç™ºè¡¨ã¯ã€ã€ŒA New GPU and De
AkihitoK 2015/04/08
deep

learning
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