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<p class="toc_title"><a href="index.html">ニューラルネットワークと深層学習</a></p><p class="toc_not_mainchapter"><a href="about.html">What this book is about</a></p><p class="toc_not_mainchapter"><a href="exercises_and_problems.html">On the exercises and problems</a></p><p class='toc_mainchapter'><a id="toc_using_neural_nets_to_recognize_handwritten_digits_reveal" class="toc_reveal" onMouseOver="this.style.borderBottom='1px solid #2A6EA6';" onMouseOut="this.style.borderBottom='0px';"><img id="toc_img_using_neural_nets_to_recognize_handwritten_digits" src="images/arrow.png" width="15px"></a><a href="chap1.html">ニューラルネットワークを用いた手書き文字認識</a><div id="toc_using_neural_nets_to_recognize_handwritten_digits" style="display: none;"><p class="toc_section"><ul><a href="chap1.html#perceptrons"><li>Perceptrons</li></a><a href="chap1.html#sigmoid_neurons"><li>Sigmoid neurons</li></a><a href="chap1.html#the_architecture_of_neural_networks"><li>The architecture of neural networks</li></a><a href="chap1.html#a_simple_network_to_classify_handwritten_digits"><li>A simple network to classify handwritten digits</li></a><a href="chap1.html#learning_with_gradient_descent"><li>Learning with gradient descent</li></a><a href="chap1.html#implementing_our_network_to_classify_digits"><li>Implementing our network to classify digits</li></a><a href="chap1.html#toward_deep_learning"><li>Toward deep learning</li></a></ul></p></div>
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});</script><p class='toc_mainchapter'><a id="toc_deep_learning_reveal" class="toc_reveal" onMouseOver="this.style.borderBottom='1px solid #2A6EA6';" onMouseOut="this.style.borderBottom='0px';"><img id="toc_img_deep_learning" src="images/arrow.png" width="15px"></a>Deep learning<div id="toc_deep_learning" style="display: none;"><p class="toc_section"><ul><li>Convolutional neural networks</li><li>Pretraining</li><li>Recurrent neural networks, Boltzmann machines, and other models</li><li>Is there a universal thinking algorithm?</li><li>On the future of neural networks</li></ul></p></div>
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});</script><p class="toc_not_mainchapter"><a href="acknowledgements.html">Acknowledgements</a></p><p class="toc_not_mainchapter"><a href="faq.html">Frequently Asked Questions</a></p>
<hr>
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<p class="sidebar">Thanks to all the <a
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Thanks also to all the contributors to the <a
href="bugfinder.html">Bugfinder Hall of Fame</a>. </p>
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<p class="sidebar">著者と共にこの本を作り出してくださった<a
href="supporters.html">サポーター</a>の皆様に感謝いたします。
また、<a
href="bugfinder.html">バグ発見者の殿堂</a>に名を連ねる皆様にも感謝いたします。
また、日本語版の出版にあたっては、<a
href="translators.html">翻訳者</a>の皆様に深く感謝いたします。
</p>
<p class="sidebar">この本は目下のところベータ版で、開発続行中です。
エラーレポートは [email protected] まで、日本語版に関する質問は [email protected] までお送りください。
その他の質問については、まずは<a
href="faq.html">FAQ</a>をごらんください。</p>
<hr>
<span class="sidebar_title">Resources</span>
<p class="sidebar">
<a href="https://github.com/mnielsen/neural-networks-and-deep-learning">Code repository</a></p>
<p class="sidebar">
<a href="http://eepurl.com/BYr9L">Mailing list for book announcements</a>
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<a href="http://eepurl.com/0Xxjb">Michael Nielsen's project announcement mailing list</a>
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<a href="http://michaelnielsen.org"><img src="assets/Michael_Nielsen_Web_Small.jpg" width="160px" style="border-style: none;"/></a>
<p class="sidebar">
著：<a href="http://michaelnielsen.org">Michael Nielsen</a> / 2014年9月-12月 <br > 訳：<a href="https://github.com/nnadl-ja/nnadl_site_ja">「ニューラルネットワークと深層学習」翻訳プロジェクト</a>
</p>
</div>
<!--<p>A big thankyou to all the supporters whose contributions have made this work possible. Supporters include:</p>-->
<p>
この本は、私(村主崇行)の監訳、と呼ぶのはおこがましい拙い、ともすれば途切れがちなお声かけのもと、以下の方々が本業と両立させながら翻訳を続けられています。
翻訳チームの皆様に感謝いたします。
</p>
<p>
<table style='border-spacing: 10px 0px;'><tr>
<tr><td><b>第一章：ニューラルネットワークを用いた手書き文字認識</b></td><td></td></tr>
<tr><td>Perceptrons</td><td>村主崇行</td></tr>
<tr><td>Sigmoid neurons</td><td>佐々木星也様,Takuya Miyamoto様</td></tr>
<tr><td>The architecture of neural networks</td><td>Takumi Motoyama様</td></tr>
<tr><td>A simple network to classify handwritten digits</td><td>Takumi Motoyama様</td></tr>
<tr><td>Learning with gradient descent</td><td>澤山高士様,佐々木辰也様</td></tr>
<tr><td>Implementing our network to classify digits</td><td>今泉智博様</td></tr>
<tr><td>Toward deep learning</td><td></td></tr>
<tr><td><b>第二章：逆伝播の仕組み</b></td><td><b>大野健太様</b></td></tr>
<tr><td>Warm up: a fast matrix-based approach to computing the output from a neural network</td><td>〃</td></tr>
<tr><td>The two assumptions we need about the cost function</td><td>〃</td></tr>
<tr><td>The Hadamard product, $s \odot t$</td><td>〃</td></tr>
<tr><td>The four fundamental equations behind backpropagation</td><td>〃</td></tr>
<tr><td>Proof of the four fundamental equations (optional)</td><td>〃</td></tr>
<tr><td>The backpropagation algorithm</td><td>〃</td></tr>
<tr><td>The code for backpropagation</td><td>〃</td></tr>
<tr><td>In what sense is backpropagation a fast algorithm?</td><td>〃</td></tr>
<tr><td>Backpropagation: the big picture</td><td>〃</td></tr>
<tr><td><b>第三章：ニューラルネットワークの学習の改善</b></td><td></td></tr>
<tr><td>The cross-entropy cost function</td><td>加藤公一様</td></tr>
<tr><td>Overfitting and regularization</td><td></td></tr>
<tr><td>Weight initialization</td><td></td></tr>
<tr><td>Handwriting recognition revisited: the code</td><td></td></tr>
<tr><td>How to choose a neural network's hyper-parameters?</td><td></td></tr>
<tr><td>Other techniques</td><td></td></tr>
<tr><td><b>第四章：ニューラルネットワークが任意の関数を表現できることの視覚的証明</b></td><td><b>大野健太様</b></td></tr>
<tr><td>Two caveats</td><td>〃</td></tr>
<tr><td>Universality with one input and one output</td><td>〃</td></tr>
<tr><td>Many input variables</td><td>〃</td></tr>
<tr><td>Extension beyond sigmoid neurons</td><td>〃</td></tr>
<tr><td>Fixing up the step functions</td><td>〃</td></tr>
<tr><td>Conclusion</td><td></td></tr>
<tr><td><b>第五章：ニューラルネットワークを訓練するのはなぜ難しいのか</b></td><td></td></tr>
<tr><td>The vanishing gradient problem</td><td></td></tr>
<tr><td>What's causing the vanishing gradient problem? Unstable gradients in deep neural nets</td><td></td></tr>
<tr><td>Unstable gradients in more complex networks</td><td></td></tr>
<tr><td>Other obstacles to deep learning</td><td></td></tr>
<tr><td><b>第六章：深層学習</b></td><td></td></tr>
<tr><td>Convolutional neural networks</td><td></td></tr>
<tr><td>Pretraining</td><td></td></tr>
<tr><td>Recurrent neural networks, Boltzmann machines, and other models</td><td></td></tr>
<tr><td>Is there a universal thinking algorithm?</td><td></td></tr>
<tr><td>On the future of neural networks</td><td></td></tr>
</table>
<p>
また、日本語訳版にパッチを下さった方々に感謝いたします。
<table style='border-spacing: 10px 0px;'>
<tr>
<td>Akihiko FUJII様</td>
<td>haru2036様</td>
<td>ANDO Yasushi様</td>
</tr><tr>
<td>neoinal様</td>
<td>Ken'ichi Matsui様</td>
<td>ITO Tetsunosuke様</td>
</tr><tr>
<td>Linus-MK様</td>
<td>hidenori-t様</td>
<td>hidenori-t様</td>
</tr><tr>
<td>MISUMI Masaru様</td>
</tr>
</table>
</p>
</table></div><div class="footer"> <span class="left_footer"> In academic work,
please cite this book as: Michael A. Nielsen, "Neural Networks and
Deep Learning", Determination Press, 2015
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