-- ·|­û / µù¥U -- ¡@
¡@±b¸¹¡G
¡@±K½X¡G
¡@ | µù¥U | §Ñ°O±K½X
3/26 ·s®Ñ¨ì¡I 3/19 ·s®Ñ¨ì¡I 3/14 ·s®Ñ¨ì¡I 12/12 ·s®Ñ¨ì¡I
ÁʮѬyµ{¡EQ & A¡E¯¸°È¯d¨¥ª©¡E«ÈªA«H½c
¢x 3ds Max¢x Maya¢x Rhino¢x After Effects¢x SketchUp¢x ZBrush¢x Painter¢x Unity¢x
¢x PhotoShop¢x AutoCad¢x MasterCam¢x SolidWorks¢x Creo¢x UG¢x Revit¢x Nuke¢x
¢x C#¢x C¢x C++¢x Java¢x ¹CÀ¸µ{¦¡¢x Linux¢x ´O¤J¦¡¢x PLC¢x FPGA¢x Matlab¢x
¢x Àb«È¢x ¸ê®Æ®w¢x ·j¯Á¤ÞÀº¢x ¼v¹³³B²z¢x Fluent¢x VR+AR¢x ANSYS¢x ²`«×¾Ç²ß¢x
¢x ³æ´¹¤ù¢x AVR¢x OpenGL¢x Arduino¢x Raspberry Pi¢x ¹q¸ô³]­p¢x Cadence¢x Protel¢x
¢x Hadoop¢x Python¢x Stm32¢x Cortex¢x Labview¢x ¤â¾÷µ{¦¡¢x Android¢x iPhone¢x
¥i¬d®Ñ¦W,§@ªÌ,ISBN,3dwoo®Ñ¸¹
¸Ô²Ó®ÑÄy¤ÀÃþ

TensorFlow­pºâ¾÷µøı­ì²z»P¹ê¾Ô

( ²Åé ¦r)
§@ªÌ¡G¼Ú¶§ÄPµ{¡B¥ô¯EµMÃþ§O¡G1. -> ±Ð§÷ -> ¼Æ¦ì¼v¹³³B²z
¡@¡@¡@2. -> µ{¦¡³]­p -> ²`«×¾Ç²ß
ĶªÌ¡G
¥Xª©ªÀ¡G²MµØ¤j¾Ç¥Xª©ªÀTensorFlow­pºâ¾÷µøı­ì²z»P¹ê¾Ô 3dWoo®Ñ¸¹¡G 54792
¸ß°Ý®ÑÄy½Ð»¡¥X¦¹®Ñ¸¹¡I

¡i¦³®w¦s¡j
NT°â»ù¡G 445 ¤¸

¥Xª©¤é¡G6/1/2021
­¶¼Æ¡G350
¥úºÐ¼Æ¡G0
¯¸ªø±ÀÂË¡G
¦L¨ê¡G¶Â¥Õ¦L¨ê»y¨t¡G ( ²Åé ª© )
¥[¤JÁʪ«¨® ¢x¥[¨ì§Úªº³Ì·R
(½Ð¥ýµn¤J·|­û)
ISBN¡G9787302579687
§@ªÌ§Ç¡@|¡@ĶªÌ§Ç¡@|¡@«e¨¥¡@|¡@¤º®e²¤¶¡@|¡@¥Ø¿ý¡@|¡@§Ç
(²Åé®Ñ¤W©Ò­z¤§¤U¸ü³sµ²¯Ó®É¶O¥\, ®¤¤£¾A¥Î¦b¥xÆW, ­YŪªÌ»Ý­n½Ð¦Û¦æ¹Á¸Õ, ®¤¤£«OÃÒ)
§@ªÌ§Ç¡G

ĶªÌ§Ç¡G

«e¨¥¡G

¤H¤u´¼¯àªº·§©À¦­¦b20¥@¬ö³Q´£¥X¡A¨äÄݤ_­pºâ¾÷¬ì¾Çªº¤@­Ó¤À¤ä¡C¦ý¬O¨ü­­¤_·í®É¦³­­ªº­pºâ¸ê·½¡A¤H¤u´¼¯à¤@ª½¥¼¯à®i²{¨ä¥¨¤jªº«Â¤O¡C¶i¤J21¥@¬ö¦Z¡AÀHµÛ¼Æ¾Ú¶qªºÃz¬µ¦¡¼Wªø»P­pºâ¸ê·½ªº´¶¹M¤Æ¡A¤H¤u´¼¯à±o¨ì¤F¥R¤Àªºµo®i¡A¦}¥B±o¨ì¤F¹êÅ窺¤ä¼µ¡C¥¦±q³Ìªì¸Õ¹Ï¼ÒÀÀ¤HÃþ¤j¸£¯«¸g¤¸¿E¬¡ªº¤è¦¡¨Ï¾÷¾¹¼Ò«¬¾Ç²ßª¾ÃѦ}²£¥ÍÃþ¦ü¤HÃþ«ä¦Òªº´¼¯à¡C
¤H¤u´¼¯à±q³Ð³y¤§©l¨ì²{¦b¡A²z½×©M§Þ³N³vº¥¦¨¼ô¡AÀ³¥Îªº»â°ì¤]¤£Â_ÂX¤j¡A±q­pºâ¾÷µøı¥ô°È¡B¦ÛµM»y¨¥³B²z¥ô°È¡B»y­µÃѧO¥ô°È¨ì±ÀÂ˺âªk³£¦³¤H¤u´¼¯àºâªkªºÀ³¥Î¡C¤H¤u´¼¯à¬O¤@ªù·¥¨ã¬D¾Ô»P«e´ºªº¬ì¾Ç¡A±q¨Æ»P¤H¤u´¼¯à¬ÛÃö¤u§@ªº¤H­û»Ý­n¥²³Æ¼Æ¾Çª¾ÃÑ¡B­pºâ¾÷ª¾ÃÑ»P¯«¸g¬ì¾Çª¾ÃÑ¡AÄݤ_¦h¾Ç¬ì¥æ¤e¿Ä¦Xªº¬ì¾Ç¡C¦b¦p¤µªñ¥G¥þ¥Á¤H¤u´¼¯àªº®É¥N¡AµL½×¬O¦b®Õ¾Ç¥ÍÁÙ¬O¤w¨B¤J¾³õªº¤u§@ªÌ¡A¤F¸Ñ¤@¨Ç¤H¤u´¼¯àªº°ò¥»ª¾ÃÑ»Pºâªk¹ï¤H¥Í³£¦³·¥¤jªºÀ°§U¡C
ÀHµÛ¤H¤u´¼¯àªº¼sªx¬y¦æ¡A¦U¤j¤¬Ápºô¥¨ÀY³£µÛ¤â¶}µo¬ÛÀ³ªº²`«×¾Ç²ß®Ø¬[¡A°ê¥~¦p¨¦ºqªºTensorFlow¡BÁy®ÑªºPyTorchµ¥¡A°ê¤º«h¦³¦Ê«×ªºPaddlePaddleµ¥¡A¨ä¤¤¦U¤j²`«×¾Ç²ß®Ø¬[³£¦U¦³Àu¶Õ¡A¥¦­Ì¹ï¤_¯à¹ê²{ªº¼Ò«¬µ²ºc¤]¦U¦³°¾¦n¡A·Q­n§¹¥þ´x´¤¦UºØ²`«×¾Ç²ß¼Ò«¬¡A¶È¶È´x´¤¤@ºØ²`«×¾Ç²ß®Ø¬[¬O§¹¥þ¤£°÷ªº¡C§@¬°¤Jªùªº²`«×¾Ç²ß®Ø¬[¡ATensorFlow¤£¥¢¬°¤@ºØ¦nªº®Ø¬[¡A¨ä¨ã¦³²M´·ªºÅÞ¿è¼h¦¸¡B¤è«Kªº¥iµø¤Æ¤u¨ã¡B§¹¾ãªºªÀ°Ï¡A¦bÀ°§UŪªÌ²z¸Ñ¼Ò«¬²Ó¸`ªº¦P®É¤è«KŪªÌ¬d¾\¬ÛÃö¸ê®Æ¦Û¦æ¾Ç²ß§ó¦hª¾ÃÑ¡C
¥»®Ñ­±¦V©Ò¦³·Q¤F¸Ñ»P¤H¤u´¼¯à¬ÛÃöª¾ÃѪºÅªªÌ¡AµL½×¬O¹s°ò¦©Î¬O¨ã¦³¤@©w°ò¦ªº¾Ç¥Í©Î¤u§@ªÌ³£¾A¥Î¡C¥»®Ñ¥HTensorFlow¬°²`«×¾Ç²ß®Ø¬[¡A¥D­nÁ¿¸Ñ­pºâ¾÷µøı¥ô°È¤¤¬ÛÃöªºª¾ÃÑ¡CTensorFlow¥Ø«e¤w§ó·s¦Ü2.xª©¡A¨ä»yªk»P§ó©ö¥ÎªºKeras¬Ûªñ¡A»PTensorFlow 1.xªº¥N½X¼gªk®t²§¸û¤j¡C¥»®Ñ©Òªö¥ÎªºTensorFlowª©¥»¬°1.14.0¡A¬OTensorFlow 1.x¤¤ªº³Ì¦Z¤@­Óª©¥»¡A¿ï¥Î¸Óª©¥»¥D­n¦³¥H¤U¨âÂI¦Ò¼{¡G ²Ä¤@¡A¥Ñ¤_TensorFlow 1.x´£¨ÑªºAPI¨ç¼Æ§ó¥[©³¼h¡A¦]¦¹¦b½s¼g¥N½X®É¯à°÷ÅýŪªÌ¯A¤Î§ó¦hªº©³¼h¹ê²{²Ó¸`¡A¤è«KŪªÌ¹ï­ì²z¥[²`²z¸Ñ¡F ²Ä¤G¡ATensorFlow 1.14.0­Ý¨ãTensorFlow 1.x»PTensorFlow 2.xªº¯S©Ê¡A¹ï¤_¥H¦Z·Q¾E²¾¨ìTensorFlow 2.xªºÅªªÌ§ó¬°¤Í¦n¡C
²Ä1©M2³¹¥D­n¬°¹s°ò¦ªºÅªªÌ³]­p¡A²Ä1³¹¤Þ¾ÉŪªÌ¦b¤£¦Pªº¾Þ§@¨t²Î¤U¥H¤£¦Pªº¤è¦¡°t¸mTensorFlow©Ò»Ýªº½sµ{Àô¹Ò¡F ²Ä2³¹¬°ÅªªÌ¤¶²Ð¤@¨Ç±`¥ÎªºPython½sµ{¤u¨ã¥]¡A³o¨Ç¤u¨ã¤£¶È¦b¤§¦Zªº³¹¸`¤¤·|¥Î¨ì¡A¦bŪªÌ¥­®É¶i¦æPython½sµ{ªº¹Lµ{¤¤¤]¤Q¤À¦³À°§U¡F ²Ä3³¹¬°¹ïTensorFlow¤£¼ô±xªºÅªªÌ³]­p¡A¹ïTensorFlow¤¤ªº¤@¨Ç¥D­n·§©À¶i¦æ¤F¤¶²Ð¡A¨Ò¦p¦p¦ó¨Ï¥ÎTensorFlow½s¼gºôµ¸¼Ò«¬ªº¿é¤J¼h¡A¦p¦ó¨Ï¥ÎTensorFlow©w¸qºôµ¸µ²ºc¦}±N¨ä¨Ï¥ÎTensorBoard¶i¦æ¥iµø¤Æµ¥¡F ²Ä4³¹ªº¤º®e§ó¥[°¾­«²z½×©Ê¡A±q¹s¶}©l¤¶²Ð²`«×¾Ç²ß¤¤ªº¤@¨Ç­«­n·§©À¡A¥]¬A¤£¦P¥ô°È¾A¥Îªº¿E¬¡¨ç¼Æ¡B·l¥¢¨ç¼Æ¡BÀu¤Æ¾¹µ¥¡A¦P®É¤¶²Ð¤F²`«×¾Ç²ß¥ô°È¤¤°V½m¼Ò«¬ªº§Þ¥©»P°Ñ¼Æªº¿ï¾Ü¡A¬Û«H³q¹L³o¨Ç§Þ¥©¡AŪªÌ¯à°÷§ó§Ö¨Ï¼Ò«¬¦¬ÀÄ¡A¹F¨ì¦Û¤v·Q­nªº®ÄªG¡F ²Ä5³¹«h­«ÂIÁ¿¸Ñ²`«×¾Ç²ß¥ô°È¤¤±`¨Ï¥Îªº¼Æ¾Ú¶°¡A±q¸û¤pªº³W«h¼Æ¾Ú¶°¨ì¼Æ¾Ú¶q¥¨¤j¦}¥B¹Ï¹³¤£³W«hªº¼Æ¾Ú¶°§¡¦³¯AÂy¡AŪªÌÀ³µÛ­«Ãöª`¹Ï¹³¤£³W«hªº¼Æ¾Ú¶°ªº¨Ï¥Î¤èªk¡A¦]¬°³o§ó±µªñ¤_¤é±`¤H­Ì¥|³B¦¬¶°¨ìªº¹Ï¹³¡A°£¦¹¥H¥~¡AÁÙµÛ­«¤¶²Ð¤F¦p¦ó±qÀY³]­p¼Æ¾Ú¶°Ãþ¡A¥]¬A¤£¦P®æ¦¡¹Ï¹³¼Æ¾ÚªºÅª¨ú»PÀò¨úµ¥¡C²Ä6~8³¹²`¤JÁ¿¸Ñ²`«×¾Ç²ß¼Ò«¬¡A±N«e5³¹¤¶²Ðªºª¾ÃÑ»P¥N½X¶i¦æ¾ã¦X¡A¥H§¹¦¨±q¼Æ¾Ú·Ç³Æ¨ì¨Ï¥Î¼Ò«¬¶i¦æ¹w´úªº¾ã­Ó¹Lµ{¡C²Ä6³¹±q³Ì²³æªº¥þ³s±µ¯«¸gºôµ¸¶}©l¡A¨Ï¥Î¨ä§¹¦¨¦^Âk»P¤ÀÃþ¥ô°È¡A±a»âŪªÌªì¨B·P¨ü¯«¸gºôµ¸ªº¾y¤O¡F ²Ä7³¹¦b¥þ³s±µ¯«¸gºôµ¸ªº°ò¦¤W¡A¥[¤J¨÷¿n¼h»PÂà¸m¨÷¿n¼h¡A¤¶²Ð¨÷¿n¯«¸gºôµ¸¡A¥H¤Î¨Ï¥Î¤£¦Pªº¨÷¿n¯«¸gºôµ¸¼Ò«¬§¹¦¨¤F³¡¤À¼Æ¾Ú¶°ªºÃѧO¥ô°È¡A¦P®ÉÁÙ¦VŪªÌ§e²{¤F¤@¨Ç¯«¸gºôµ¸¼Ò«¬¤ñ¸û¦³½ìªºÀ³¥Î¡A¦p¨Ï¹Ï¹³§ó²M´·¡B¬°¶Â¥Õ¹Ï¹³¤W¦âµ¥¡F ²Ä8³¹¦b¨÷¿n¯«¸gºôµ¸ªº°ò¦¤W¨Ï¥Î¤£¦Pªº²z½×°²³]¡A¨Ï¼Ò«¬§¹¦¨¹Ï¹³¥Í¦¨ªº¥ô°È¡A³q¹L¹ï¨âºØ¸g¨å¥Í¦¨¦¡¼Ò«¬ªº¤¶²Ð¡A¬Û«HŪªÌ¯à¹ï¯«¸gºôµ¸¼Ò«¬ªºÀ³¥Î³õ´º¦h¤@¼h²z¸Ñ¡C
¥»®Ñªº¤º®e¤Q¤À³s³e¡A¨C­Ó³¹¸`ªº¤º®e³£·|¨Ï¥Î¨ì«e­±³¹¸`Á¿¸Ñ¹Lªºª¾ÃÑ¡A¦®¦b³Ì¤j­­«×«OÃÒŪªÌ¾Ç²ßªº³s³e©Ê¡A¦P®É¥»®Ñ±N±âÀßÃøÀ´ªº¼Æ¾Ç¤½¦¡´î¨ì³Ì¤Ö¡AºÉ¤O¥H¹Ï¥Üªº¤è¦¡«P¶iŪªÌ²z¸Ñ¡A¥»®Ñ³¡¤À±m¹Ï½Ð¨£´¡­¶¡C¬Û«HŪªÌŪ§¹¥»®Ñ¦Z·|¹ï­pºâ¾÷µøı¬ÛÃö¥ô°È¦³¤@­Ó§ó²M´·ªº²z¸Ñ¡A§Æ±æ¥»®Ñ¯à¦¨¬°¨C¤@¦ìŪªÌ¥´¶}²`«×¾Ç²ß»PTensorFlowªºª÷Æ_°Í¡C
½sªÌ2021¦~1¤ë


¥»®Ñ·½¥N½X¤U¸ü
¤º®e²¤¶¡G

¥»®Ñ¥HPython¼Æ¾Ú³B²z¤u¨ã©M²`«×¾Ç²ßªº°ò¥»­ì²z¬°¤Á¤JÂI¡A¥Ñ²L¤J²`¤¶²ÐTensorFlowªº¨Ï¥Î¤èªk¡C¥Ñ­ì²zµÛ¤â¨ì¥N½X¹ê½î¡A¤º®e±q³Ì°ò¥»ªº¦^Âk°ÝÃD¶}©l¡A¨ìªñ¦~¨Ó¤j¼öªº¨÷¿n¯«¸gºôµ¸©M¥Í¦¨¦¡¼Ò«¬¡C¥»®Ñ¬Ù¥h¤j¶q·Ðº¾ªº¼Æ¾Ç±À¾É¡A¥H³q«U©öÀ´ªº»y¨¥©M¥Ü¨ÒÄÄ­z²`«×¾Ç²ßªº­ì²z¡C
¥»®Ñ¦@8³¹¡A²Ä1©M2³¹¤¶²ÐTensorFlowªºÀô¹Ò·f«Ø»PPython°ò¥»¼Æ¾Ú³B²z¤u¨ã¡A¬°¦Z­±¤¶²ÐTensorFlow°µ·Ç³Æ¡F²Ä3~5³¹Á¿¸ÑTensorFlow©M²`«×¾Ç²ß¤¤ªº°ò¥»·§©À¤Î²`«×¾Ç²ß±`¥Î¼Æ¾Ú¶°¡F²Ä6~8³¹±q©ö¨ìÃø²`¤JÁ¿¸Ñ¤£¦Pªº¯«¸gºôµ¸¼Ò«¬¦}°t¦X¤j¶qªº¥Ü¨Ò¡A¶i¤@¨B¾d©TTensorFlow¥N½Xªº¨Ï¥Î¡C¥»®Ñ°t¦³¾ã®M¥N½X¡A¦b­«ÂI¡BÃøÂI³B°t¦³Á¿¸ÑµøÀW¡AŪªÌ¥i¥H®Ú¾Ú¦Û¨­¿³½ì»P»Ý¨D¹ï¥N½X¶i¦æ­×§ï¦}³q¹LµøÀW¹ïÃø¥H²z¸Ñªºª¾ÃÑÂI¶i¦æ¾d©T¡C
¥»®ÑªºÃø«×¡B¼h¦¸²M´·¡A¾A¦X¥ô¦ó§Æ±æ¤Jªù¤H¤u´¼¯à»â°ìªº¾Ç¥Í©Î¤u§@ªÌ¾\Ū¡A¦P®É¤]¥]§t·sªº§Þ³N¡A¾A¤_·Q­nºò¸òµøı¬ã¨sªº±q·~¤H­û¾\Ū¡C
¥Ø¿ý¡G

²Ä1³¹²`«×¾Ç²ß²¤¶¤ÎTensorFlowÀô¹Ò·f«Ø¡]21min¡^
1.1¤°¤\¬O²`«×¾Ç²ß
1.2²`«×¾Ç²ß»y¨¥»P¤u¨ã
1.3TensorFlowªºÀu¶Õ
1.4TensorFlowªº¦w¸Ë»PÀô¹Ò°t¸m
1.4.1Windows¤U°t¸mGPUª©TensorFlow
1.4.2Linux¤U°t¸mGPUª©TensorFlow
1.4.3ª½±µ³q¹LAnaconda¸Ñ¨MÀô¹Ò¨Ì¿à
1.4.4¦w¸ËCPUª©¥»ªºTensorFlow
1.5¤pµ²
²Ä2³¹±`¥ÎªºPython¼Æ¾Ú³B²z¤u¨ã
2.1NumPyªº¨Ï¥Î
2.1.1NumPy¤¤ªº¼Æ¾ÚÃþ«¬
2.1.2NumPy¤¤¼Æ²Õªº¨Ï¥Î
2.2Matplotlibªº¨Ï¥Î
2.2.1Matplotlib¤¤ªº¬ÛÃö·§©À
2.2.2¨Ï¥ÎMatplotlibø¹Ï
2.3Pandasªº¨Ï¥Î
2.3.1Pandas¤¤ªº¼Æ¾Úµ²ºc
2.3.2¨Ï¥ÎPandasŪ¨ú¼Æ¾Ú
2.3.3¨Ï¥ÎPandas³B²z¼Æ¾Ú
2.4SciPyªº¨Ï¥Î
2.4.1¨Ï¥ÎSciPy¼g¤Jmat¤å¥ó
2.4.2¨Ï¥ÎSciPyŪ¨úmat¤å¥ó
2.5scikitúQlearnªº¨Ï¥Î
2.5.1scikitúQlearnªº¨Ï¥Î®Ø¬[
2.5.2¨Ï¥ÎscikitúQlearn¶i¦æ¦^Âk
2.5.3¨Ï¥ÎscikitúQlearn¶i¦æ¤ÀÃþ
2.6Pillowªº¨Ï¥Î
2.6.1¨Ï¥ÎPillowŪ¨ú¦}Åã¥Ü¹Ï¹³
2.6.2¨Ï¥ÎPillow³B²z¹Ï¹³
2.7OpenCVªº¨Ï¥Î
2.7.1¨Ï¥ÎOpenCVŪ¨ú»PÅã¥Ü¹Ï¹³
2.7.2¨Ï¥ÎOpenCV³B²z¹Ï¹³
2.8argparseªº¨Ï¥Î
2.8.1argparseªº¨Ï¥Î®Ø¬[
2.8.2¨Ï¥Îargparse¸ÑªR©R¥O¦æ°Ñ¼Æ
2.9JSONªº¨Ï¥Î
2.9.1¨Ï¥ÎJSON¼g¤J¼Æ¾Ú
2.9.2¨Ï¥ÎJSONŪ¨ú¼Æ¾Ú
2.10¤pµ²
²Ä3³¹TensorFlow°ò¦
3.1TensorFlowªº°ò¥»­ì²z
3.2TensorFlow¤¤ªº­pºâ¹Ï»P·|¸Ü¾÷¨î
3.2.1­pºâ¹Ï
3.2.2·|¸Ü¾÷¨î
3.3TensorFlow¤¤ªº±i¶qªí¥Ü
3.3.1tf.constant
3.3.2tf.Variable
3.3.3tf.placeholder
3.4TensorFlow¤¤ªº¼Æ¾ÚÃþ«¬
3.5TensorFlow¤¤ªº©R¦WªÅ¶¡
3.5.1tf.get_variable
3.5.2tf.name_scope
3.5.3tf.variable_scope
3.6TensorFlow¤¤ªº±±¨î¬y
3.6.1TensorFlow¤¤ªº¤À¤äµ²ºc
3.6.2TensorFlow¤¤ªº´`Àôµ²ºc
3.6.3TensorFlow¤¤«ü©w¸`ÂI°õ¦æ¶¶§Ç
3.7TensorFlow¼Ò«¬ªº¿é¤J»P¿é¥X
3.8TensorFlowªº¼Ò«¬«ù¤[¤Æ
3.8.1¼Ò«¬ªº«O¦s
3.8.2¼Ò«¬ªºÅª¨ú
3.9¨Ï¥ÎTensorBoard¶i¦æµ²ªG¥iµø¤Æ
3.9.1­pºâ¹Ïªº¥iµø¤Æ
3.9.2¥Ú¶qÅܤƪº¥iµø¤Æ
3.9.3¹Ï¹³ªº¥iµø¤Æ
3.10¤pµ²
²Ä4³¹²`«×¾Ç²ßªº°ò¥»·§©À¡]108min¡^
4.1²`«×¾Ç²ß¬Û¸û¤_¶Ç²Î¤èªkªºÀu¶Õ
4.2²`«×¾Ç²ß¤¤ªº¿E¬¡¨ç¼Æ
4.2.1Sigmoid
4.2.2Softmax
4.2.3Tanh
4.2.4ReLU
4.2.5LeakyReLU
4.2.6PReLU
4.2.7RReLU
4.2.8ReLUúQ6
4.2.9ELU
4.2.10Swish
4.2.11Mish
4.3²`«×¾Ç²ß¤¤ªº·l¥¢¨ç¼Æ
4.3.1¦^Âk¥ô°È
4.3.2¤ÀÃþ¥ô°È
4.4²`«×¾Ç²ß¤¤ªºÂk¤@¤Æ/¼Ð·Ç¤Æ¤èªk
4.4.1Âk¤@¤Æ¤èªk
4.4.2¼Ð·Ç¤Æ¤èªk
4.5²`«×¾Ç²ß¤¤ªºÀu¤Æ¾¹
4.5.1¤£±a°Ê¶qªºÀu¤Æ¾¹
4.5.2±a°Ê¶qªºÀu¤Æ¾¹
4.6²`«×¾Ç²ß¤¤ªº§Þ¥©
4.6.1¿é¤J¼Æ¾Úªº³B²z
4.6.2¿E¬¡¨ç¼Æªº¿ï¾Ü
4.6.3·l¥¢¨ç¼Æªº¿ï¾Ü
4.6.4¼Ð·Ç¤Æ¤èªkªº¿ï¾Ü
4.6.5batch_sizeªº¿ï¾Ü
4.6.6Àu¤Æ¾¹ªº¿ï¾Ü
4.6.7¾Ç²ß²vªº¿ï¾Ü
4.7¤pµ²
²Ä5³¹±`¥Î¼Æ¾Ú¶°¤Î¨ä¨Ï¥Î¤è¦¡
5.1IRIS»ð§Àªá¼Æ¾Ú¶°
5.2MNIST¤â¼g¼Æ¦r¼Æ¾Ú¶°
5.3SVHN¼Æ¾Ú¶°
5.4CIFARúQ10»PCIFARúQ100¼Æ¾Ú¶°
5.4.1CIFARúQ10
5.4.2CIFARúQ100
5.4.3¹ï¹Ï¹³¶i¦æ¼Æ¾Ú¼W±j
5.5OxfordFlower¼Æ¾Ú¶°
5.6ImageNet¼Æ¾Ú¶°
5.7¤pµ²
²Ä6³¹¥þ³s±µ¯«¸gºôµ¸
6.1¤°¤\¬O¥þ³s±µ¯«¸gºôµ¸
6.1.1·Pª¾¾÷
6.1.2¥þ³s±µ¯«¸gºôµ¸
6.2¨Ï¥Î¥þ³s±µ¯«¸gºôµ¸¶i¦æ¦^Âk
6.3¨Ï¥Î¥þ³s±µ¯«¸gºôµ¸¶i¦æ¤ÀÃþ
6.4¨Ï¥Î¥þ³s±µ¯«¸gºôµ¸¹ï¼Æ¾Ú­°ºû
6.5¨Ï¥Î¥þ³s±µ¯«¸gºôµ¸§¹¦¨¤â¼g¼Æ¦rÃѧO
6.5.1°V½m¼Ò«¬
6.5.2«O¦sÅv­«
6.5.3¥æ¤¬±µ¦¬¥Î¤á¿é¤J
6.5.4¥[¸üÅv­«¦}¹w´ú
6.6¤pµ²
²Ä7³¹¨÷¿n¯«¸gºôµ¸¡]77min¡^
7.1¤°¤\¬O¨÷¿n
7.1.1¨÷¿nªº·§©À
7.1.2¨÷¿n¾Þ§@ªº°Ñ¼Æ
7.1.3¨÷¿nªº­pºâ¤è¦¡
7.2¨÷¿n¯«¸gºôµ¸¤¤±`¥Îªº¼h
7.2.1¿é¤J¼h
7.2.2¨÷¿n¼h
7.2.3¿E¬¡¼h
7.2.4¼Ð·Ç¤Æ¼h
7.2.5¦À¤Æ¼h
7.2.6¥þ³s±µ¼h
7.3±`¥Îªº¨÷¿n¯«¸gºôµ¸µ²ºc
7.3.1VGGNet
7.3.2Inception
7.3.3ResNet
7.3.4DenseNet
7.3.5ResNeXt
7.3.6MobileNet
7.3.7DualPathNetwork
7.3.8SENet
7.3.9SKNet
7.3.10ResNeSt
7.4¨Ï¥Î¨÷¿n¯«¸gºôµ¸§¹¦¨¹Ï¹³¤ÀÃþ
7.4.1©w¸q©R¥O¦æ°Ñ¼Æ
7.4.2¼Ò«¬°V½m¨ç¼Æ
7.4.3¼Ò«¬´ú¸Õ¨ç¼Æ
7.4.4¥D¨ç¼Æ
7.4.5°V½m¼Ò«¬ÃѧO¤â¼g¼Æ¦r
7.4.6°V½m¼Ò«¬ÃѧO¦ÛµM³õ´º¹Ï¹³
7.5¨÷¿n¯«¸gºôµ¸¨s³º¾Ç¨ì¤F¤°¤\
7.5.1¨÷¿n®Öªº¥iµø¤Æ
7.5.2Ãþ¿E¬¡¬M®gªº¥iµø¤Æ
7.5.3¨÷¿n¯«¸gºôµ¸¿é¥X¹w´ú­Èªº¥iµø¤Æ
7.6¨Ï¥Î¨÷¿n¯«¸gºôµ¸µ¹¥þ³s±µ¯«¸gºôµ¸¶Ç±Âª¾ÃÑ
7.7Âà¸m¨÷¿n¼h
7.7.1¤°¤\¬OÂà¸m¨÷¿n¼h
7.7.2¨Ï¥ÎÂà¸m¨÷¿n¼hÅý¹Ï¹³Åܱo²M´·
7.7.3¨Ï¥ÎÂà¸m¨÷¿n¼hµ¹¹Ï¹³¤W¦â
7.8¨Ï¥Î¨÷¿n¼h»P¤Ï¨÷¿n¼h°µ¦Û½s½X¾¹
7.9¤pµ²
²Ä8³¹¥Í¦¨¦¡¼Ò«¬
8.1¤°¤\¬O¥Í¦¨¦¡¼Ò«¬
8.2ÅܤÀ¦Û½s½X¾¹
8.2.1¤°¤\¬OÅܤÀ¦Û½s½X¾¹
8.2.2¨Ï¥ÎÅܤÀ¦Û½s½X¾¹¥Í¦¨¤â¼g¼Æ¦r
8.2.3¨Ï¥ÎÅܤÀ¦Û½s½X¾¹¥Í¦¨«ü©wªº¼Æ¦r
8.3¥Í¦¨¦¡¹ï§Üºôµ¸
8.3.1¤°¤\¬O¥Í¦¨¦¡¹ï§Üºôµ¸
8.3.2¨Ï¥Î¥Í¦¨¦¡¹ï§Üºôµ¸¥Í¦¨¤â¼g¼Æ¦r
8.3.3¨Ï¥Î¥Í¦¨¦¡¹ï§Üºôµ¸¥Í¦¨«ü©wªº¼Æ¦r
8.3.4¨Ï¥Î¥Í¦¨¦¡¹ï§Üºôµ¸¥Í¦¨¦ÛµM¹Ï¹³
8.3.5¨Ï¥Î¥Í¦¨¦¡¹ï§Üºôµ¸¶i¦æ¹Ï¹³°ìÂà´«
8.4¤pµ²
§Ç¡G