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<h1>
[Neural Networks and Deep Learning] week1. Introduction to deep learning
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<time datetime="2017-09-11T00:00:00+02:00"><i class="fa fa-calendar"></i> Mon, 11 Sep 2017</time>
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<span class="label label-default">Series</span>
Part 1 of «Andrew Ng Deep Learning MOOC»
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目录
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<div id="toc"><ul><li><a class="toc-href" href="#what-is-a-neural-network" title="What is a neural network?">What is a neural network?</a></li><li><a class="toc-href" href="#supervised-learning-with-neural-networks" title="Supervised Learning with Neural Networks">Supervised Learning with Neural Networks</a></li><li><a class="toc-href" href="#why-is-deep-learning-taking-off" title="Why is Deep Learning taking off?">Why is Deep Learning taking off?</a></li><li><a class="toc-href" href="#about-this-course" title="About this course">About this course</a></li></ul></div>
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<h2 id="what-is-a-neural-network">What is a neural network?</h2>
<p>Example: housing price prediciton. </p>
<p>Each neuron: ReLU function</p>
<p>Stacking multiple layers of neurons: hidden layers are concepts more general than input layer — found automatically by NN.<br/>
<img alt="" class="img-responsive" src="../images/Ng_DLMooc_c1wk1/pasted_image.png"/></p>
<h2 id="supervised-learning-with-neural-networks">Supervised Learning with Neural Networks</h2>
<p>supervised learning: during training, always have output corresponding to input.</p>
<p>Different NN types are used for different problems:<br/>
<img alt="" class="img-responsive" src="../images/Ng_DLMooc_c1wk1/pasted_image002.png"/></p>
<p><img alt="" class="img-responsive" src="../images/Ng_DLMooc_c1wk1/pasted_image003.png"/></p>
<p>structured data: database, each feature/column has a well-defined meaning.
unstructured data: audio/image/text, no well-defined meaning for pixels/tokens</p>
<h2 id="why-is-deep-learning-taking-off">Why is Deep Learning taking off?</h2>
<p><strong>scale</strong> drives deep learning progress.
(scale: both of NN and of data)</p>
<p>trandition methods: pleateaus as amount of data grows further.
NN: grows with data.<br/>
<img alt="" class="img-responsive" src="../images/Ng_DLMooc_c1wk1/pasted_image005.png"/></p>
<ul>
<li>data scales up </li>
<li>computation faster</li>
<li>new algorithms, e.g. from sigmoid to ReLU, which in turn speeds up computation too. </li>
</ul>
<h2 id="about-this-course">About this course</h2>
<p><img alt="" class="img-responsive" src="../images/Ng_DLMooc_c1wk1/pasted_image007.png"/></p>
<p>This course: <strong>implementing</strong> NN.<br/>
<img alt="" class="img-responsive" src="../images/Ng_DLMooc_c1wk1/pasted_image006.png"/></p>
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Part 1 of series «Andrew Ng Deep Learning MOOC»：
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<li class="list-group-item"><a class="btn btn-primary" href='https://x-wei.github.io/Ng_DLMooc_c1wk1.html' style="text-align:left">[Neural Networks and Deep Learning] week1. Introduction to deep learning</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c1wk2.html' style="text-align:left">[Neural Networks and Deep Learning] week2. Neural Networks Basics</a></li>
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<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c2wk3.html' style="text-align:left">[Improving Deep Neural Networks] week3. Hyperparameter tuning, Batch Normalization and Programming Frameworks</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c3wk1.html' style="text-align:left">[Structuring Machine Learning Projects] week1. ML Strategy (1)</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c3wk2.html' style="text-align:left">[Structuring Machine Learning Projects] week2. ML Strategy (2)</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c4wk1.html' style="text-align:left">[Convolutional Neural Networks] week1. Foundations of Convolutional Neural Networks</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c4wk2.html' style="text-align:left">[Convolutional Neural Networks] week2. Deep convolutional models: case studies</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c4wk3.html' style="text-align:left">[Convolutional Neural Networks] week3. Object detection</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c4wk4.html' style="text-align:left">[Convolutional Neural Networks] week4. Special applications: Face recognition & Neural style transfer</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c5wk1.html' style="text-align:left">[Sequential Models] week1. Recurrent Neural Networks</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c5wk2.html' style="text-align:left">[Sequential Models] week2. Natural Language Processing & Word Embeddings</a></li>
<li class="list-group-item"><a class="btn btn-default" href='https://x-wei.github.io/Ng_DLMooc_c5wk3.html' style="text-align:left">[Sequential Models] week3. Sequence models & Attention mechanism</a></li>
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