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ÇØ¿ÜÁÖ¹®/¹Ù·Îµå¸²/Á¦ÈÞ»çÁÖ¹®/¾÷ü¹è¼Û°ÇÀÇ °æ¿ì 1+1 ÁõÁ¤»óǰÀÌ ¹ß¼ÛµÇÁö ¾Ê½À´Ï´Ù.
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    2022.06.24 ~ 2022.07.31
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ISBN 9788997924585(8997924583)
Âʼö 320ÂÊ
Å©±â 189 * 258 * 16 mm /669g ÆÇÇü¾Ë¸²

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ÅÙ¼­Ç÷οì 2.x ±â¹ÝÀÇ ½Ç½ÀÇü µö·¯´× ÀÔ¹®¼­´Ù. ÃʱÞÀÚ¿ë ½Ç½À¿¹Á¦ 165°³¸¦ ¼ö·ÏÇß°í ½ÇÀü ¿¬½À¹®Á¦ 15°³¸¦ ½º½º·Î Ç®¾îº»´Ù¸é µö·¯´× ÃʱÞÀ» Å»ÃâÇÏ¿© ½º½º·Î ÇнÀÇÒ ÁÙ ¾Æ´Â µ¶ÀÚ·Î °Åµì³¯ ¼ö ÀÖÀ» °ÍÀÌ´Ù. ´Ù¸¥ ÇÁ·Î±×·¡¹Ö ÀÔ¹®¼­¿Í °°ÀÌ µö·¯´× ÇнÀ ¶ÇÇÑ ¹Ýº¹ ½Ç½À¸¸ÀÌ ÀÔ¹® ´Ü°è¸¦ ¹þ¾î³ª±â À§ÇÑ °¡Àå ºü¸¥ ¹æ¹ýÀÌ´Ù. ÀÌ Ã¥ÀÌ Á¦½ÃÇÏ´Â ÇнÀ ¹æ¹ýÀÎ, µ¥ÀÌÅ͸¦ ¼öÁýÇÏ°í ¸ðµ¨À» ¸¸µé¸ç ÇнÀÀ» ½ÃŰ´Â ÆÐÅÏÀ» ²ÙÁØÇÏ°Ô ¹Ýº¹ ÇнÀÇÏ´Ù º¸¸é ´ÙÀ½ ´Ü°è·Î ³ª¾Æ°¡´Â ±æÀ» ãÀ» ¼ö ÀÖÀ» °ÍÀÌ´Ù.

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µö·¯´×À» óÀ½ °øºÎÇϰíÀÚ ÇÏ´Â ÇлýÀ̳ª °³¹ßÀÚ
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¹é°ßºÒ¿©ÀÏŸ µö·¯´× ÀÔ¹® with ÅÙ¼­Ç÷οì 2.x µµ¼­ »ó¼¼À̹ÌÁö

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ÁöÀºÀÌÀÇ ±Û
ÆíÁýÀÚÀÌÀÚ º£Å¸Å×½ºÅÍÀÇ ±Û
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1Àå ÁغñÇϱâ
1.1 ½ÃÀÛÇϸç
1.2 Äɶ󽺶õ
1.3 ÄÉ¶ó½º ÁغñÇϱâ
1.4 ¹«·á Ŭ¶ó¿ìµå »ç¿ëÇϱâ
1.5 API ¹®¼­ Ȱ¿ëÇϱâ
Á¤¸®Çغ¾½Ã´Ù

[ÇÔ²² ÇØºÁ¿ä] ÅÙ¼­Ç÷ο츦 ¼³Ä¡ÇÒ °¡»óȯ°æ ¸¸µé¾î º¸±â
[ÇÔ²² ÇØºÁ¿ä] ÅÙ¼­Ç÷οì CPU ¹öÀü ¼³Ä¡Çϱâ
[ÇÔ²² ÇØºÁ¿ä] ÅÙ¼­Ç÷οì GPU ¹öÀü ¼³Ä¡¿Í Å×½ºÆ®
[ÇÔ²² ÇØºÁ¿ä] ±¸±Û µå¶óÀÌºê ¿¬µ¿Çϱâ
[ÇÔ²² ÇØºÁ¿ä] ij±Û ³ëÆ®ºÏ¿¡¼­ °á°ú¹° ¾ò´Â ¹æ¹ý

2Àå »ìÆìº¸±â
2.1 ¸Ó½Å·¯´× ÇÁ·Î¼¼½º °£·«È÷ »ìÆìº¸±â
2.2 ¿ë¾î »ìÆìº¸±â
2.3 µ¥ÀÌÅͼ »ìÆìº¸±â
2.4 Ä¿¹Â´ÏƼ »ìÆìº¸±â
Á¤¸®Çغ¾½Ã´Ù

[ÇÔ²² ÇØºÁ¿ä] ÀÓÀǷΠŬ·¡½º È®·üÀ» ÁöÁ¤ÇÏ¿© ±×¸° ROC °î¼± (chapter02/roccurve.py)

3Àå ±âº»±â ´ÙÁö±â
3.1 ±âº» ¿¬»ê ÇØº¸±â
3.2 ½Å°æ¸Á
3.3 Äɶ󽺿¡¼­ÀÇ °³¹ß °úÁ¤
Á¤¸®Çغ¾½Ã´Ù
½Ç½ÀÇØº¾½Ã´Ù

[ÇÔ²² ÇØºÁ¿ä] ÅÙ¼­ÀÇ Â÷¿ø°ú ±âº» ¿¬»ê (basic_calc.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Áï½Ã ½ÇÇà ¸ðµå¸¦ ÅëÇÑ ¿¬»ê (basic_calc.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÅÙ¼­¿¡¼­ ³ÑÆÄÀÌ·Î, ³ÑÆÄÀÌ¿¡¼­ ÅÙ¼­·Î (basic_calc.ipynb)
[ÇÔ²² ÇØºÁ¿ä] @tf.function (basic_calc.ipynb)
[ÇÔ²² ÇØºÁ¿ä] OR °ÔÀÌÆ® ±¸ÇöÇØº¸±â (perceptron.ipynb)
[ÇÔ²² ÇØºÁ¿ä] º¤ÅÍÀÇ ³»Àû (perceptron.ipynb)
[ÇÔ²² ÇØºÁ¿ä] XOR °ÔÀÌÆ® ±¸ÇöÇØº¸±â + ´ÙÃþ ÆÛ¼ÁÆ®·Ð (perceptron.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¿©·¯ °¡Áö Ȱ¼ºÈ­ ÇÔ¼ö (perceptron.ipynb)
[ÇÔ²² ÇØºÁ¿ä] °æ»çÇϰ­¹ý ½ÇÇèÇØº¸±â (perceptron.ipynb)

4Àå ½Å°æ¸Á Àû¿ëÇØº¸±â
4.1 MNIST¿Í Fashion-MNIST
4.2 º¸½ºÅÏ ÁÖÅà °¡°Ý ¿¹Ãø
4.3 ºù»êÀΰ¡? ¼±¹ÚÀΰ¡?-1
¡®³ªÀÇ ÀÌÇØµµ¸¦ ÃøÁ¤ÇÏÀÚ¡¯ 3¹ø ¹®Á¦
4.4 ¹«½¼ ¿Ê°ú ¹«½¼ »ö?-1
Á¤¸®Çغ¾½Ã´Ù
½Ç½ÀÇØº¾½Ã´Ù
¹ø¿Ü_ij±ÛÀ» ÅëÇØ ´É·Â Çâ»ó½Ã۱â

[ÇÔ²² ÇØºÁ¿ä] MNIST µ¥ÀÌÅͼ ´Ù¿î¹Þ±â (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍÀÇ ÇüÅ ȮÀÎÇϱâ (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ ±×·Áº¸±â (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] °ËÁõ µ¥ÀÌÅÍ ¸¸µé±â (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÀÔ·ÂÀ» À§ÇÑ µ¥ÀÌÅÍ Àüó¸® (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÀÔ·ÂÀ» À§ÇÑ ·¹À̺í Àüó¸® (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ±¸¼ºÇϱâ (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¼ÒÇÁÆ®¸Æ½º¿Í ½Ã±×¸ðÀÌµå °ªÀÇ ºñ±³ (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇнÀ°úÁ¤ ¼³Á¤Çϱâ (mnist.pynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÇнÀÇϱâ (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] history¸¦ ÅëÇØ È®ÀÎÇØº¼ ¼ö ÀÖ´Â °ª Ãâ·ÂÇϱâ (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇнÀ °á°ú ±×·Áº¸±â (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ Æò°¡Çϱâ (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇнÀµÈ ¸ðµ¨À» ÅëÇØ °ª ¿¹ÃøÇϱâ (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¿¹Ãø°ª ±×·Á¼­ È®ÀÎÇØº¸±â (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ Æò°¡ ¹æ¹ý 1?È¥µ¿Çà·Ä (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ Æò°¡ ¹æ¹ý?2 ºÐ·ù º¸°í¼­ (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] MNIST µ¥ÀÌÅͼ ´Ù·ç±â: Àüü ÄÚµå (mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Fashion-MNIST µ¥ÀÌÅͼ ´Ù¿î¹Þ±â (fashion-mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ ±×·Áº¸±â (fashion-mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Àüó¸® ¹× °ËÁõ µ¥ÀÌÅͼ ¸¸µé±â (fashion-mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ù ¹øÂ° ¸ðµ¨ ±¸¼ºÇϱâ (fashion-mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇнÀ °úÁ¤ ¼³Á¤ ¹× ÇнÀÇϱâ (fashion-mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µÎ ¹øÂ° ¸ðµ¨ ±¸¼ºÇϱâ (fashion-mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µÎ ¸ðµ¨ÀÇ ÇнÀ °úÁ¤ ±×·Áº¸±â (fashion-mnist.ipynb)
[ÇÔ²² ÇØºÁ¿ä] º¸½ºÅÏ ÁÖÅà °¡°Ý µ¥ÀÌÅͼ ´Ù¿î¹Þ±â (boston.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ ÇüÅ ȮÀÎÇϱâ (boston.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ Àüó¸® ¹× °ËÁõ µ¥ÀÌÅͼ ¸¸µé±â (boston.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ±¸¼ºÇϱâ (boston.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇнÀÇÏ°í Æò°¡Çϱâ (boston.ipynb)
[ÇÔ²² ÇØºÁ¿ä] K-Æúµå »ç¿ëÇϱâ (boston.ipynb)
[ÇÔ²² ÇØºÁ¿ä] K-Æúµå °á°ú È®ÀÎÇϱâ (boston.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ ºÒ·¯¿À±â (clothes1.ipynb)
[ÇÔ²² ÇØºÁ¿ä] À̹ÌÁö Á¦³×·¹ÀÌÅÍ Á¤ÀÇ ¹× ¸ðµ¨ ±¸¼ºÇϱâ (clothes1.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ Á¦³×·¹ÀÌÅÍ Á¤ÀÇÇϱâ (clothes1.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Á¦³×·¹ÀÌÅ͸¦ ÅëÇØ ¸ðµ¨ ÇнÀ½Ã۱â (clothes1.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Å×½ºÆ® µ¥ÀÌÅÍ ¿¹ÃøÇϱâ (clothes1.ipynb)

5Àå ÄÁº¼·ç¼Ç ½Å°æ¸Á
5.1 ÀÏ´Ü »ç¿ëÇØº¸±â
5.2 ÄÁº¼·ç¼ÇÃþ°ú Ç®¸µÃþ
5.3 CIFAR-10 »ìÆìº¸±â
5.4 ºù»êÀΰ¡? ¼±¹ÚÀΰ¡??2
¡®³ªÀÇ ÀÌÇØµµ¸¦ ÃøÁ¤ÇÏÀÚ¡¯ 3¹ø ¹®Á¦
5.5 ÀüÀÌ ÇнÀ
Á¤¸®Çغ¾½Ã´Ù
½Ç½ÀÇØº¾½Ã´Ù

[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ »ìÆìº¸±â (fashion_mnist_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ±¸¼ºÇϱâ (fashion_mnist_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÇнÀ½Ã۱â (fashion_mnist_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] À̹ÌÁö ÇÊÅÍ »ç¿ëÇØº¸±â (use_image_filter.ipynb)
[ÇÔ²² ÇØºÁ¿ä] À̹ÌÁö ÇÊÅÍ Á¤ÀÇÇϱâ (use_image_filter.ipynb)
[ÇÔ²² ÇØºÁ¿ä] À̹ÌÁö ÇÊÅÍ Àû¿ëÇϱâ (use_image_filter.ipynb)
[ÇÔ²² ÇØºÁ¿ä] À̹ÌÁö ÇÊÅ͸¦ Àû¿ëÇÑ ÃÖÁ¾ °á°ú (use_image_filter.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Ç®¸µ ¿¬»ê ±¸ÇöÇϱâ (use_image_filter.ipynb)
[ÇÔ²² ÇØºÁ¿ä] model.summary( ) ÇÔ¼ö »ç¿ëÇϱâ
[ÇÔ²² ÇØºÁ¿ä] plot_model( ) ÇÔ¼ö »ç¿ëÇϱâ
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 µ¥ÀÌÅͼ ´Ù¿î¹Þ±â (cifar10_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 µ¥ÀÌÅÍ ±×·Áº¸±â (cifar10_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 µ¥ÀÌÅͼ Àüó¸® °úÁ¤ (cifar10_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 ¸ðµ¨ ±¸¼ºÇϱâ (cifar10_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 ¸ðµ¨ ÇнÀÇϱâ (cifar10_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 ÇнÀ °úÁ¤ ±×·Áº¸±â (cifar10_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ½Å°æ¸Á ½Ã°¢È­Çغ¸±â (cifar10_cnn.ipynb)
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 ±ÔÁ¦È­ ÇÔ¼ö »ç¿ëÇØº¸±â (drop_the_overfitting_regularizer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 µå·Ó¾Æ¿ô »ç¿ëÇØº¸±â (drop_the_overfitting_dropout.ipynb)
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 ¹èÄ¡ Á¤±ÔÈ­ »ç¿ëÇØº¸±â (drop_the_overfitting_BN.ipynb)
[ÇÔ²² ÇØºÁ¿ä] À̹ÌÁö Á¦³×·¹ÀÌÅ͸¦ »ç¿ëÇÏ¿© À̹ÌÁö ±×·Áº¸±â (basic_image_generator.ipynb)
[ÇÔ²² ÇØºÁ¿ä] À̹ÌÁö Á¦³×·¹ÀÌÅ͸¦ »ç¿ëÇÏ¿© ¸ðµ¨ ÇнÀÇϱâ (basic_image_generator.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÀüÀÌ ÇнÀ »ç¿ëÇØº¸±â (basic_transfer_learning.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ µ¿°á ÇØÁ¦Çϱâ
[ÇÔ²² ÇØºÁ¿ä] ÀüÀÌ ÇнÀÀ» ÅëÇØ ÇнÀÇϱâ (basic_transfer_learning.ipynb)

6Àå ¼øÈ¯ ½Å°æ¸Á
6.1 Embedding
6.2 RNN
6.3 LSTM
6.4 Conv1D
6.5 BERT °¡º±°Ô ¾Ë¾Æº¸±â
Á¤¸®Çغ¾½Ã´Ù
½Ç½ÀÇØº¾½Ã´Ù

[ÇÔ²² ÇØºÁ¿ä] Åäūȭ ÀÛ¾÷ ¼öÇàÇϱâ (use_embedding_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅͼ ´Ù¿î¹Þ±â (use_embedding_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ ÇüÅ ȮÀÎÇϱâ (use_embedding_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ù ¹øÂ° µ¥ÀÌÅÍ È®ÀÎÇϱâ (use_embedding_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] IMDB µ¥ÀÌÅͼ¿¡¼­ °¡Àå ºó¹øÇÏ°Ô »ç¿ëµÇ´Â ¼¼ °³ÀÇ ´Ü¾î
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅ͸¦ µ¿ÀÏÇÑ ±æÀÌ·Î ¸ÂÃß±â (use_embedding_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] EmbeddingÃþÀ» »ç¿ëÇÏ¿© ¸ðµ¨ ±¸¼ºÇϱâ (use_embedding_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÇнÀ½Ã۱â (use_embedding_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ Æò°¡Çϱâ (use_embedding_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇнÀ °úÁ¤ È®ÀÎÇϱâ (use_embedding_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] cos ÇÔ¼ö¸¦ ÀÌ¿ëÇÏ¿© µ¥ÀÌÅÍ ¸¸µé±â (use_SimpleRNN_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Àüó¸® °úÁ¤ ¼öÇàÇϱâ (use_SimpleRNN_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ ÇüÅ ȮÀÎÇϱâ (use_SimpleRNN_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] SimpleRNNÀ» »ç¿ëÇÏ¿© ¸ðµ¨ ±¸¼ºÇϱâ (use_SimpleRNN_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÇнÀ½Ã۱â (use_SimpleRNN_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¿¹Ãø °á°ú ±×·Áº¸±â (use_SimpleRNN_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] IMDB µ¥ÀÌÅͼ »ç¿ëÇϱâ (use_SimpleRNN_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] SimpleRNNÃþÀÇ Ãâ·Â°ª º¯È­ È®ÀÎÇϱâ (use_SimpleRNN_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] reuters µ¥ÀÌÅͼ ´Ù·ïº¸±â (use_LSTM_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅͼ Àüó¸® °úÁ¤
[ÇÔ²² ÇØºÁ¿ä] LSTM ÃþÀ» »ç¿ëÇÏ¿© ¸ðµ¨ ±¸¼ºÇϱâ (use_LSTM_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÇнÀ½Ã۱â (use_LSTM_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Conv1D ÃþÀ» »ç¿ëÇÏ¿© ¸ðµ¨ ±¸¼ºÇϱâ (use_Conv1D_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÇнÀ½Ã۱â (use_Conv1D_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅÍ »ý¼ºÇϱâ (use_Conv1D_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ±¸¼º ¹× °á°ú È®ÀÎÇϱâ (use_Conv1D_layer.ipynb)

7Àå ÃʱÞÀ» ÇâÇØ¼­-1
7.1 Äɶó½ºÀÇ ¸ðµ¨ ±¸¼º ¹æ¹ý
7.2 ÇÔ¼öÇü API
7.3 ºù»êÀΰ¡? ¼±¹ÚÀΰ¡?-3
¡®³ªÀÇ ÀÌÇØµµ¸¦ ÃøÁ¤ÇÏÀÚ¡¯ 1¹ø ¹®Á¦
7.4 ¹«½¼ ¿Ê°ú ¹«½¼ »ö?-2
7.5 ÄÉ¶ó½º Äݹé
Á¤¸®Çغ¾½Ã´Ù
½Ç½ÀÇØº¾½Ã´Ù

[ÇÔ²² ÇØºÁ¿ä] Sequential( ) ¸ðµ¨ ±¸¼º (make_model_three_ways.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¼­ºêŬ·¡½Ì ¸ðµ¨ ±¸¼º (make_model_three_ways.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇÔ¼öÇü API ¸ðµ¨ ±¸¼ºÇϱâ (make_model_three_ways.ipynb)
[ÇÔ²² ÇØºÁ¿ä] MNIST µ¥ÀÌÅͼ ºÒ·¯¿À±â ¹× Àüó¸® (functional_api_MNIST.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇÔ¼öÇü API¸¦ Ȱ¿ëÇÑ ¸ðµ¨ ±¸¼º ¹× ÇнÀ (functional_api_MNIST.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ´ÙÁß ÀÔÃâ·ÂÀ» À§ÇÑ µ¥ÀÌÅÍ »ý¼ºÇϱâ (functional_api_multi_io.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ´ÙÁß ÀÔÃâ·Â ¸ðµ¨ ±¸¼ºÇϱâ (functional_api_multi_io.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ±¸Á¶ ±×·Áº¸±â (functional_api_multi_io.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ±¸Á¶ È®ÀÎÇϱâ (functional_api_multi_io.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ´ÙÁß ÀÔÃâ·Â ¸ðµ¨¿¡¼­ ÇнÀ °úÁ¤ ¼³Á¤Çϱâ (functional_api_multi_io.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ´ÙÁß ÀÔÃâ·Â ¸ðµ¨ ÇнÀÇϱâ (functional_api_multi_io.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÀÜÂ÷ ¿¬°áÀ» »ç¿ëÇÏ¿© ¸ðµ¨ ±¸¼ºÇϱâ (residual_and_inception_module.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÀμÁ¼Ç ¸ðµâÀ» »ç¿ëÇÏ¿© ¸ðµ¨ ±¸¼ºÇϱâ (residual_and_inception_module.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ResNetÀ» Ȱ¿ëÇÏ¿© ¸ðµ¨ ±¸¼ºÇϱâ (resnet_transfer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÅÙ¼­Ç÷οì Çãºê ¼³Ä¡Çϱâ
[ÇÔ²² ÇØºÁ¿ä] CIFAR-10 µ¥ÀÌÅͼ ºÒ·¯¿À±â (use_tensorflow_hub.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Àüü ¸ðµ¨ ±¸¼ºÇϱâ (use_tensorflow_hub.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÇнÀ½Ã۱â (use_tensorflow_hub.ipynb)
[ÇÔ²² ÇØºÁ¿ä] (clothes_classification/clothes3.csv)
[ÇÔ²² ÇØºÁ¿ä] (clothes_classification/clothes3.csv)
[ÇÔ²² ÇØºÁ¿ä] (clothes_classification/clothes3.csv)
[ÇÔ²² ÇØºÁ¿ä] ÄÉ¶ó½º ÄÝ¹é »ç¿ë ÁغñÇϱâ (use_keras_callbacks.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ModelCheckpoint ÄÝ¹é »ç¿ëÇϱâ (use_keras_callbacks.ipynb)
[ÇÔ²² ÇØºÁ¿ä] EarlyStopping ÄÝ¹é »ç¿ëÇϱâ (use_keras_callbacks.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ReduceLROnPlateau ÄÝ¹é »ç¿ëÇϱâ (use_keras_callbacks.ipynb)
[ÇÔ²² ÇØºÁ¿ä] TensorBoard ÄÝ¹é »ç¿ëÇϱâ (use_keras_callbacks.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÅÙ¼­º¸µå ½ÇÇàÇϱâ - 1
[ÇÔ²² ÇØºÁ¿ä] ÅÙ¼­º¸µå ½ÇÇàÇϱâ- 2

8Àå ÃʱÞÀ» ÇâÇØ¼­-2
8.1 Ä¿½ºÅ͸¶ÀÌÁ¦À̼Ç
8.2 1¡¿1 ÄÁº¼·ç¼Ç
8.3 ÃÊ±Þ ´Ü°è¸¦ À§ÇØ ÇѰÉÀ½ ´õ
Á¤¸®Çغ¾½Ã´Ù
½Ç½ÀÇØº¾½Ã´Ù

[ÇÔ²² ÇØºÁ¿ä] Lambda Ãþ »ç¿ëÇϱâ (custom_keras_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Ä¿½ºÅÒ Äɶó½ºÃþ »ç¿ëÇϱâ (custom_keras_layer.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Activation ÇÔ¼ö¿¡ Á÷Á¢ Àü´ÞÇÏ´Â ¹æ¹ý (custom_activation.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Ä¿½ºÅÒ °´Ã¼ ¸ñ·ÏÀ» »ç¿ëÇÏ´Â ¹æ¹ý - 1 (custom_activation.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Ä¿½ºÅÒ °´Ã¼ ¸ñ·ÏÀ» »ç¿ëÇÏ´Â ¹æ¹ý ? 2 (custom_activation.ipynb)
[ÇÔ²² ÇØºÁ¿ä] RAdam ¼³Ä¡Çϱâ
[ÇÔ²² ÇØºÁ¿ä] RAdamÀÇ Á¸Àç ¾Ë±â (custom_activation.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Ä¿½ºÅÒ ¼Õ½Ç ÇÔ¼ö Á¤ÀÇÇϱâ (custom_loss.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Ä¿½ºÅÒ ¼Õ½Ç ÇÔ¼ö?MNIST ÇнÀ (custom_loss.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Ä¿½ºÅÒ Æò°¡ÁöÇ¥ Á¤ÀÇÇÏ¿© »ç¿ëÇϱâ (custom_metrics.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ƯÁ¤ ½ÃÁ¡¿¡ ÇнÀ·üÀ» Á¶Á¤ÇÏ´Â Ä¿½ºÅÒ ÄÉ¶ó½º Äݹé (custom_callback.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Ä¿½ºÅÒ ÄÉ¶ó½º ÄݹéÀ» »ç¿ëÇÏ¿© ¸ðµ¨ ÇнÀ½Ã۱â (custom_callback.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÄÁº¼·ç¼ÇÃþ¸¸À¸·Î ±¸¼ºÇÑ ¸ðµ¨ - 1 (MNIST_1¡¿1_convolution.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÄÁº¼·ç¼ÇÃþ¸¸À¸·Î ±¸¼ºÇÑ ¸ðµ¨ - 2 (MNIST_1¡¿1_convolution.ipynb)

9Àå ÄÉ¶ó½º Æ©³Ê
9.1 Ž»öÇØ¾ß ÇÒ ÇÏÀÌÆÛÆÄ¶ó¹ÌÅÍ
9.2 ÄÉ¶ó½ºÆ©³Ê »ç¿ëÇϱâ
9.3 ÄÉ¶ó½ºÆ©³Ê ´õ ½±°Ô »ç¿ëÇϱâ
Á¤¸®Çغ¾½Ã´Ù
½Ç½ÀÇØº¾½Ã´Ù

ºÎ·Ï A: ¿ÀÅäÄɶó½º(AutoKeras)
ºÎ·Ï B: tf.data
ºÎ·Ï C: ÀÌ·¸°Ôµµ ÇнÀÇÒ ¼ö ÀÖ¾î¿ä!

[ÇÔ²² ÇØºÁ¿ä] °£´ÜÇÑ ±¸Á¶ÀÇ CNN ¸ðµ¨ »ìÆìº¸±â (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÄÉ¶ó½º Æ©³Ê ¼³Ä¡Çϱâ
[ÇÔ²² ÇØºÁ¿ä] ÄÉ¶ó½º Æ©³Ê ¸ðµ¨ Á¤ÀÇÇϱâ (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] MNIST µ¥ÀÌÅͼ ÁغñÇϱâ (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] RandomSearch Ŭ·¡½º »ç¿ëÇϱâ (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] Ž»öÇÒ ÇÏÀÌÆÛÆÄ¶ó¹ÌÅÍ »ìÆìº¸±â (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇÏÀÌÆÛÆÄ¶ó¹ÌÅÍ Å½»öÇϱâ (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ½ÇÇè °á°ú ¿ä¾àÇØº¸±â (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] °¡Àå ÁÁÀº ¼º´ÉÀÇ ¸ðµ¨ ºÒ·¯¿À±â (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ÇÏÀÌÆÛÆÄ¶ó¹ÌÅÍ È®ÀÎÇϱâ (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] HyperResNet »ç¿ëÇϱâ (keras_tuner_example.ipynb)
[ÇÔ²² ÇØºÁ¿ä] (clothes_classification/tf_data_example.py)
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅͼ ºÒ·¯¿À±â ()appendix/training_with_tensorflow2.0.ipynb
[ÇÔ²² ÇØºÁ¿ä] µ¥ÀÌÅͼ °´Ã¼ Á¤ÀÇÇϱâ ()appendix/training_with_tensorflow2.0.ipynb
[ÇÔ²² ÇØºÁ¿ä] ¸ðµ¨ ±¸¼ºÇϱâ (appendix/training_with_tensorflow2.0.ipynb)
[ÇÔ²² ÇØºÁ¿ä] °´Ã¼ Á¤ÀÇÇϱâ (appendix/training_with_tensorflow2.0.ipynb)
[ÇÔ²² ÇØºÁ¿ä] °è»ê ¹ß»ý ÁöÁ¤Çϱâ (appendix/training_with_tensorflow2.0.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇнÀ ¹× °ËÁõ ½ºÅÜ Á¤ÀÇÇϱâ (appendix/training_with_tensorflow2.0.ipynb)
[ÇÔ²² ÇØºÁ¿ä] ÇнÀ ÁøÇàÇϱâ (appendix/training_with_tensorflow2.0.ipynb)

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