The best of CES 2025Presenting our 12 finalists, plus the winner of our best in show award.
ãã®ã¨ããDeep Learningãç¸å½æµè¡ã£ã¦ããããã§ãã»ã¨ãã©è³ãã¨ããã§è©±é¡ã«ãªã£ã¦ããã®ãè¦ã¾ãã Deep Learningã¯æ·±å±¤å¦ç¿ã¨ãå¼ã°ãããã¥ã¼ã©ã«ãããã¯ã¼ã¯ã®å±¤ãããã¾ã§ããæ·±ããã¦æ©æ¢°å¦ç¿ãè¡ãææ³ã§ãï¼ã ããã§ãï¼ã ç»åèªèã³ã³ãã¹ãã§ä»ã®æ¹æ³ã¨æ¯ã¹ã¦é常ã«é«ã精度ã示ãã¦ããã以åã¯äººã®æã§è¡ã£ã¦ããç¹å¾´ã®æ½åºã¾ã§è¡ãã¾ãã 以åã§ããã°è»ãèªèããã«ã¯è»ã¯ã©ã®ãããªç¹å¾´ãæã£ã¦ãããã人ãã¢ãã«åãã¦å ¥åãã¦ããããã§ããããã®ç¹å¾´ãå ¥åç»åã¨ä¸ããããã©ãã«ãããã¥ã¼ã©ã«ãããã¯ã¼ã¯ãæãã¦ããã¾ãã詳ãããã¨ã¯Deep Learningã§æ¤ç´¢ãã¦åºã¦ããè¨äºãã¹ã©ã¤ããåç §ã®ãã¨ã Deep Learningèªä½ã¯å®¹æã«å®è£ å¯è½ãªãã®ã§ã¯ãªãããã§ãããå¤ãã®ç 究ã°ã«ã¼ããDeep Learningãè¡ãããã®ã½ããã¦ã§ã¢ããªã¼ãã³ã½ã¼ã¹ã«ãã¦ããã
https://github.com/Songmu/App-LJ ljã¨ãããã¼ã«ãæ¸ãããæ¨æºå ¥åãèªãã§JSONã½ãæååãå«ã¾ãã¦ãããè²ä»ãã§ç¶ºéºã«åºãã¦ãããããããªæãã fluentdã§stdoutã§åºãããã°ã¨ããã¢ããªã±ã¼ã·ã§ã³ããéã«JSONã§åãããã°ãçºããã¨ãã¨ãã«ä¾¿å©ã % cpanm App::LJ ã§å ¥ãã¾ãããfatpackããåä¸ãã¡ã¤ã«ãä½ã£ã¦ããã®ã§ã以ä¸ã®ããã«ãã¦ã使ãã¾ãã % curl -L https://raw.githubusercontent.com/Songmu/App-LJ/master/lj > /usr/local/bin/lj; chmod +x /usr/local/bin/lj fatpack㯠@ks0608 ããã®App::Fatpack::Simpleã使ã£ãã便å©ãCPANã«ããã¦æ¬²ããã å®è£ ã ãã¶éãªã®ã§ãã
File::RotateLogs ã大å¤ä¾¿å©ã§ãã使ã£ã¦ããã®ã ããããã¯ãã¡ã¤ã«ã¸æ¸ãè¾¼ãã¨ãã« print ãå¼ãã§ããã ä¸æ¹ ã«ã²ããã::ããã·ã - perl ã§å¾©æ°ã®ããã»ã¹ãããã°ãåãã¨ã㯠syswrite ã¾ã㯠flock ãã¹ã ã«ããã¨é·ããã°ãåãã¨ã㯠syswrite ã«ããªãã¨æ··ããã¨ããã ãã£ã¦ File::RotateLogs ãå®ã¯æ··ãããã¨ãããã®ããªã¨æããè¤æ°ããã»ã¹ããé·ããã°ãåãã¾ãã£ã¦ã¿ããä¸åã«æ··ãããªãã£ãã ãããã調ã¹ãçµæãopen layer ã«æãä½ç´ãª layer ã§ãã :unix ãæå®ããã° print æã 1 ã¤ã® write(2) ã«ãªãããã ã£ãã > cat test.pl open my $fh, ">:unix", "test.txt"; print $fh "a" x (1024 * 100);
Conwayâs game of Life may be mathematically interesting, but it is not what most people would consider a real game. So letâs take a look at another product of the 70âs, the arcade game Snake. This post walks through a complete, compile time implementation of a Snake game using C++ template metaprogramming. Weâll start by implementing a basic list and grid, before moving on to encode the game rules
AI & MLLearn about artificial intelligence and machine learning across the GitHub ecosystem and the wider industry. Generative AILearn how to build with generative AI. GitHub CopilotChange how you work with GitHub Copilot. LLMsEverything developers need to know about LLMs. Machine learningMachine learning tips, tricks, and best practices. How AI code generation worksExplore the capabilities and be
大éã®ãã¼ã¿ã®èå¾ã«ããæ½å¨çãªæ å ±ãæ½åºããæè¡ã¨ãã¦ï¼ãããã¯ã¢ãã«ã¨å¼ã°ããçµ±è¨ã¢ãã«ã®ç 究ãè¿å¹´æ³¨ç®ãéãã¦ãããæ¬æ¸ã¯ããã«ã¤ãã¦ï¼è¨èªå¦çã¨ããå ·ä½çãªåé¡ã«å¯¾ãã¦ï¼ãã®çè«ã¨å¿ç¨ããããããã解説ããã 0. æ¬æ¸ã®ä½¿ãæ¹ 0.1ã æ¬æ¸ã®èªã¿æ¹ 0.2ã åç« ã¨ä»é²ã®èª¬æ 0.3ã æ¬æ¸ã§ç¨ããè¨å·ãªã© 1. çµ±è¨çæ½å¨æå³è§£æã¨ã¯ 1.1 ãæ½å¨çæå³ã»ãããã¯ã¨æ½å¨çå ±èµ·æ§ 1.2 ãæ½å¨æå³è§£æã®æ´å² 1.3 ãçµ±è¨çæ½å¨æå³è§£æã¨ãã¼ã¿é§åã¤ã³ããªã¸ã§ã³ã¹ã®åµçº 1.4ã 確ççæ½å¨å¤æ°ã¢ãã« 1.5 ã確çççæã¢ãã«ã¨ã°ã©ãã£ã«ã«ã¢ãã« 2. Latent Dirichlet Allocation 2.1ã æ¦è¦ 2.2 ãå¤é åå¸ã¨Dirichletåå¸ 2.3 ãLDAã®çæéç¨ 2.4ã LDAã®å¹¾ä½å¦ç解é 2.5ã LDAã®å¿ç¨ä¾ 3. å¦ç¿ã¢ã«ã´ãªãº
ãªãªã¼ã¹ãé害æ å ±ãªã©ã®ãµã¼ãã¹ã®ãç¥ãã
ææ°ã®äººæ°ã¨ã³ããªã¼ã®é ä¿¡
j次ã®ããã¯ãã¼ã¯
kåã®ããã¯ãã¼ã¯
lãã¨ã§èªã
eã³ã¡ã³ãä¸è¦§ãéã
oãã¼ã¸ãéã
{{#tags}}- {{label}}
{{/tags}}