ãå¦ã³ãã«ãã´ãªã§ãããã³ããªãé£çºãã人æ°ããã¬ã¼ è¿« 使¨¹ï¼id:McGï¼ããã®ææ°ã¨ã³ããªã¼ã§ãããã¡ãã«â¦
ãã®æã®ããªã§ãããªãã³ã¡ãæå ¥ããããæãã®ã»ãå¤ãã®ã¹ã¿ã¼ãããã ãã¾ããããããã¨ããããã¾ããã
ãã³ã¬ã§è¶ èªã¿ããã確ççµ±è¨ã®ãªã¹ã¹ã¡åèæ¸ãã¡ - ããããã»ITé飿¥è¨
ããã³ã¬ã§ãããæ©æ¢°å¦ç¿ãã£ã¦ã®ãæãã¦ãããããããï¼
2017/07/01 01:21
å人çãªäºæ ã ããä½ã¶æãåãã ãã¼ãããä½ãDeep Learning âPythonã§å¦ã¶ãã£ã¼ãã©ã¼ãã³ã°ã®çè«ã¨å®è£ ãã¨ããæ¬ãèªãã§ãæ©æ¢°å¦ç¿ã®åå¼·ããã¦ãããããã«å人çãªäºæ ã«ãªããããã¾ãã¾ãã®ã¨ã³ããªã¼ãèªãç´åã«ãèªåãªãã®ãã¬ã¼ã¯ã¹ã«ã¼ãä½é¨ãã¦é«æãã¦ããããããããªãã¨ãæ¸ãã¦ãã¾ã£ãã®ã ããã¬ã¼ã¯ã¹ã«ã¼ã¨ããã®ã¯ãã¨ã¦ãé£ããã¨æãã¦ããç®æã«å¯¾ããç·´ç¿åé¡ãèªä½ãã¦è§£ãã¦ã¿ãã¨ãã使¥ãç¹°ãè¿ãããã¨ã«ããããçè§£ãããã¨ãã宿ãå¾ãã¨ããæå³ã ã
ã¹ãã³ãµã¼ãªã³ã¯
Â
Â
ãã³ãã³ç¹°ãè¿ãã¦ããããã«ãå¼ããã°ã®ä¸»ç®çã¯èªåç¨ã®ã¡ã¢ã ã1000人ã«è¿ãæ¹ã«èªè ç»é²ãã¦ããã ãã¦ã大å¤ãããããæãã¦ãããã䏿¹ã§ç³ã訳ãªããæãã¦ãããã ããèªåã®åå¼·ã«é¢ããã¡ã¢ãªã©ãä¸è¬æ§ããã¾ããªãã¨æã£ãå 容ã®ã¨ã³ããªã¼ã¯ãæ¥ä»ãããã®ã¼ã£ã¦å ¬éãããã¨ã«ãã¦ãããããããã¨ãæ°çãããç®ç«ã¡ã«ãããªãã®ã ã
ãããå ã«è¿°ã¹ããããªãã¨ããã£ãã®ã§ããããããªã§ã䏿²æ¸ã«é¢ããä¸é£ã®ã¡ã¢çã¨ã³ããªã¼ã®ãã¡æå¾ã®ãã®ã ãããææ°ã®æ¥ä»ã§å ¬éãã¦ã¿ãããããååã®ã¨ã³ããªã¼ã§ããã
ããããããæãã®ã»ãå¤ãã®ã¹ã¿ã¼ã¨ããã¯ãã¼ã¯ãããã ããä¹ ãã¶ãã«ããã¯ããã¸ã¼ãã«ãã´ãªã§ãããã³ããªå ¥ããã¦ãã¾ã£ããããã¾ã§èªåç¨ã¡ã¢ã®ã¤ããã§ãèªè ã¸ã®ååãªé æ ®ããããªã£ã¦ããã¨ã¯è¨ããªãã¨ã³ããªã¼ã ã£ãã®ã§ããããããããç³ã訳ãªãã¨ããææ ãå ã«ç«ã£ããè¬ã£ã¦ããã¾ãããã¿ã¾ããã
Â
ããã䏿¹ã§ãããã¯ãæ©æ¢°å¦ç¿ã§ããã¨ããAIã§ããã¨ããããã®ãããããããã¨ããéè¦ãããã¨ãããã¨ãªã®ã§ã¯ãªããã¨ãèããã
ã¿ããªä¸å®ãªããããªããã¨æã£ãã
AIããã¼ã ã®ããã«ãªã£ã¦ãããããªãã¿ã®ãªããã®ãå¾ä½ã®ç¥ããªããã®ãããã£ã¨ããéã«èº«ã®åãã«æ¼ãå¯ãããããæªæ¥ã大ããå¤ãã¦ãã¾ãããã§ãããã¨ã«ãã¿ããªä¸å®ãæãã¦ããããããªããã¨æ³åããã
ããã¦AIã¨ãæ©æ¢°å¦ç¿ã¨ããããã®ã®å®ä½ã«é¢ããããããããã説æãããã°ãããããä¸å®ãå°ãã¯è§£æ¶ãããããããªãã ãããã
ã ãããããã³ã¬ã§ãããæ©æ¢°å¦ç¿ãã¨ããã®ã®ãã¼ã ããããªããæ¬æ°ã§æãã¦å ¬éããããã¨æãã¤ããããããã©ãããããã ãããã©ãããããã®ã¯æ©ãè åã¡çãªã¨ãããããã®ã§ã
ç§ã®çè§£ãã¦ããç¯å²ã§ã¯ãæ©æ¢°å¦ç¿ã®åçã¯ã髿 ¡æ°å¦ã®è¡åæ¼ç®ã¨å¾®åæ³ãããã«è¥å¹²ã®ããã°ã©ãã³ã°ã®ç¥èãããã°ãããç¨åº¦ã¤ã¡ã¼ã¸ã¤ãããããããªããã¨æããã¤ããããç§ã«çè§£ã§ããéçã§ããããã ããééã£ã¦ããããç¥ããªãã
ãã£ã¨è¨ãã¨ãç§ã®ç¥èã®ç¯å²ã ã¨ãæ©æ¢°å¦ç¿ã¯æããããå¶å¾¡å·¥å¦ã®çè«ã«ãã¨ã¦ãããä¼¼ã¦ããã¨æãããããã¯é«æ ¡æ°å¦ã§ã¯è¶³ãã大å¦ã®å¦é¨ã¬ãã«ã®é£æåº¦ã«ãªããã ããçè§£ãã¦ããã¨ã¯è¨ã£ã¦ãªããã§ããæãããã£ã¦ãã§ã«ãããå®ç¨ããã¦ãããã®ããããã¹ã®è¡£è£ ãå¤ãã¦èå°ã«åç»å ´ããããã«ãè¦ãããã¨ãããã¨ã¯å®ã¯ãæã ã®ä½ã社ä¼ã¯å¦ãå¿ããªããã§ã«å¤§ããå½±é¿ããã¦ããããã®æªæ¥ãå½±é¿ãåãã¦ã©ãã©ãå¤ãããã¤ã¤ããã¨ãè¨ãããã ã
ããããã«ç´ 人è¸ã ã¨è¨ãããããã ãããã¯ã¦ãªããã°ãã§ããã°ããã³ãªãã¨ãæ¸ãã°å³åº§ã«ãã³ã¡ã§çªã£è¾¼ã¿ãå ¥ãããããã§ãããã¨éãç´ãã
ãã¨ãç§ã®ç»åã¯ãã®ç¨åº¦ã ãã©ã
ãããããç§ã®æ©æ¢°å¦ç¿ã®ç¥èã¯ã»ã¨ãã©ããã¼ãããä½ãDeep Learningãã«ä¾åãã¦ããã®ã§ãããã¡ãã£ã¨ç¥è¦ãåºããããæåã©ããã®ãã¬ã¼ã ã¯ã¼ã¯ã®1ã¤ã2ã¤ã¯ããã£ã¦ãããªãã¡ãã¨æã£ã¦ããã
ãã ãæãã¤ããããã¨ãããã8æã«å ¥ã£ã¦ããã«ãªããåºæ¬ãæäººãªãã ãã©ãä»ã¯çããã¤ãä»äºãç«ã¦è¾¼ãã§ãææãªã®ã§ã
èªã¿ããã§ããï¼
ã¢ã¤ãã£ããç»åã«ããããããããã¨ã ããããç´ æãåããã¾ããã
人工ç¥è½ã¨æ¦ãå°æ£ã®æ£å£«ã®ã¤ã©ã¹ã | ããããããªã¼ç´ æé ãããã¨ã
ã¹ãã³ãµã¼ãªã³ã¯
Â