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By darkday AI(人工ç¥è½)ã大ããªè©±é¡ã¨ãªã£ã¦ããã³ã³ãã¥ã¼ã¿ã¼ãµã¤ã¨ã³ã¹ã®ä¸çã§ããã®æè¡ãæ¯ãã¦ããã®ãããã£ã¼ãã©ã¼ãã³ã°ãã§ããä¸æ¹ãã³ã³ãã¥ã¼ã¿ã¼ã使ã£ããæ©æ¢°å¦ç¿ãã¨ããè¨èãè³ã«ãããã¨ãå¤ããã®ã§ãããå®ã¯ãã®éããããããããªã人ãå¤ãã¯ãããããªä¸¡è ã®éãããæ°å¦çè¨ç®ã½ããã¦ã§ã¢ãMATLABãã®éçºå ã§ããMathWorksãç°¡åã«è§£èª¬ãã¦ãã¾ãã Introduction to Deep Learning: Machine Learning vs Deep Learning - YouTube æ©æ¢°å¦ç¿ããã£ã¼ãã©ã¼ãã³ã°ããå¦ç¿ã¢ãã«ãæä¾ãã¦ãã¼ã¿ãåé¡ãããã¨ã«ä½¿ãããæè¡ã§ãããã®åãã解説ããã®ã«ããç¨ããããã®ããç¬ã¨ç«ã®ç»åãåé¡ããã¨ããä¾ããã®ç»åã®å ´åãã»ã¼å ¨ã¦ã®äººãå·¦ãç¬ãå³ãç«ã¨çããã¯ãã ããããå¥ã®ç»åãæã£ã¦ããæããã
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1. tiny-dnn is a header-only deep learning framework for C++ that aims to be easy to introduce, have simple syntax, and support extensible backends. 2. It allows defining neural networks concisely using modern C++ features and supports common network types like MLPs and CNNs through simple syntax similar to Keras and TensorFlow. 3. The framework has optional performance-oriented backends like AVX
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