mhjensen
259 lines
12 KiB
HTML
259 lines
12 KiB
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<a class="navbar-brand" href="week42-bs.html">Week 42 Convolutional (CNN) and Recurrent (RNN) Neural Networks</a>
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<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
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<ul class="dropdown-menu">
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<!-- navigation toc: --> <li><a href="._week42-bs001.html#___sec0" style="font-size: 80%;">Plan for week 42</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs002.html#___sec1" style="font-size: 80%;">Convolutional Neural Networks (recognizing images)</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs003.html#___sec2" style="font-size: 80%;">Neural Networks vs CNNs</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs004.html#___sec3" style="font-size: 80%;">Why CNNS for images, sound files, medical images from CT scans etc?</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs005.html#___sec4" style="font-size: 80%;">Regular NNs don’t scale well to full images</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs006.html#___sec5" style="font-size: 80%;">3D volumes of neurons</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs007.html#___sec6" style="font-size: 80%;">Layers used to build CNNs</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs008.html#___sec7" style="font-size: 80%;">Transforming images</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs009.html#___sec8" style="font-size: 80%;">CNNs in brief</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs010.html#___sec9" style="font-size: 80%;">CNNs in more detail, building convolutional neural networks in Tensorflow and Keras</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs011.html#___sec10" style="font-size: 80%;">Setting it up</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs012.html#___sec11" style="font-size: 80%;">The MNIST dataset again</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs013.html#___sec12" style="font-size: 80%;">Strong correlations</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs014.html#___sec13" style="font-size: 80%;">Layers of a CNN</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs015.html#___sec14" style="font-size: 80%;">Systematic reduction</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs016.html#___sec15" style="font-size: 80%;">Prerequisites: Collect and pre-process data</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs017.html#___sec16" style="font-size: 80%;">Importing Keras and Tensorflow</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs018.html#___sec17" style="font-size: 80%;">Running with Keras</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs019.html#___sec18" style="font-size: 80%;">Final part</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs020.html#___sec19" style="font-size: 80%;">Final visualization</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs021.html#___sec20" style="font-size: 80%;">The CIFAR01 data set</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs022.html#___sec21" style="font-size: 80%;">Verifying the data set</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs023.html#___sec22" style="font-size: 80%;">Set up the model</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs024.html#___sec23" style="font-size: 80%;">Add Dense layers on top</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs025.html#___sec24" style="font-size: 80%;">Compile and train the model</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs026.html#___sec25" style="font-size: 80%;">Finally, evaluate the model</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs027.html#___sec26" style="font-size: 80%;">Recurrent neural networks: Overarching view</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs028.html#___sec27" style="font-size: 80%;">Set up of an RNN</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs029.html#___sec28" style="font-size: 80%;">A simple example</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs030.html#___sec29" style="font-size: 80%;">An extrapolation example</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs031.html#___sec30" style="font-size: 80%;">Formatting the Data</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs032.html#___sec31" style="font-size: 80%;">Predicting New Points With A Trained Recurrent Neural Network</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs033.html#___sec32" style="font-size: 80%;">Other Things to Try</a></li>
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<!-- navigation toc: --> <li><a href="._week42-bs034.html#___sec33" style="font-size: 80%;">Other Types of Recurrent Neural Networks</a></li>
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<a name="part0000"></a>
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<!-- ------------------- main content ---------------------- -->
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<div class="jumbotron">
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<center><h1>Week 42 Convolutional (CNN) and Recurrent (RNN) Neural Networks</h1></center> <!-- document title -->
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<p>
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<!-- author(s): Morten Hjorth-Jensen -->
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<center>
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<b>Morten Hjorth-Jensen</b> [1, 2]
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</center>
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<p>
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<!-- institution(s) -->
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<center>[1] <b>Department of Physics, University of Oslo</b></center>
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<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
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<br>
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<p>
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<center><h4>Oct 17, 2020</h4></center> <!-- date -->
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<br>
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<p>
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<p><a href="._week42-bs001.html" class="btn btn-primary btn-lg">Read »</a></p>
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<li class="active"><a href="._week42-bs000.html">1</a></li>
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<li><a href="._week42-bs001.html">2</a></li>
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<li><a href="._week42-bs002.html">3</a></li>
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<li><a href="._week42-bs003.html">4</a></li>
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<li><a href="._week42-bs004.html">5</a></li>
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<li><a href="._week42-bs005.html">6</a></li>
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<li><a href="._week42-bs006.html">7</a></li>
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<li><a href="._week42-bs007.html">8</a></li>
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<li><a href="._week42-bs008.html">9</a></li>
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<li><a href="._week42-bs009.html">10</a></li>
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<li><a href="">...</a></li>
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<li><a href="._week42-bs034.html">35</a></li>
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<li><a href="._week42-bs001.html">»</a></li>
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<center style="font-size:80%">
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<!-- copyright --> © 1999-2020, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
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