update week42
This commit is contained in:
Morten Hjorth-Jensen
@@ -1,15 +1,15 @@
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<meta name="description" content="Week 42 Convolutional (CNN) and Recurrent (RNN) Neural Networks">
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<meta name="description" content="Week 42 Solving differential equations and Convolutional (CNN)">
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<title>Week 42 Convolutional (CNN) and Recurrent (RNN) Neural Networks</title>
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<title>Week 42 Solving differential equations and Convolutional (CNN)</title>
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||||
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|
||||
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|
||||
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|
||||
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|
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||||
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<body>
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@@ -130,7 +251,7 @@ MathJax.Hub.Config({
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<span class="icon-bar"></span>
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<span class="icon-bar"></span>
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</button>
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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 class="navbar-brand" href="week42-bs.html">Week 42 Solving differential equations and Convolutional (CNN)</a>
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</div>
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<div class="navbar-collapse collapse navbar-responsive-collapse">
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@@ -138,40 +259,81 @@ MathJax.Hub.Config({
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<li class="dropdown">
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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>
|
||||
<!-- 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>
|
||||
<!-- 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>
|
||||
<!-- 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>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs032.html#___sec31" style="font-size: 80%;">Predicting New Points With A Trained Recurrent Neural Network</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs033.html#___sec32" style="font-size: 80%;">Other Things to Try</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs034.html#___sec33" style="font-size: 80%;">Other Types of Recurrent Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs001.html#plan-for-week-42" style="font-size: 80%;">Plan for week 42</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs002.html#using-automatic-differentiation" style="font-size: 80%;">Using Automatic differentiation</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs003.html#solving-odes-with-deep-learning" style="font-size: 80%;">Solving ODEs with Deep Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs004.html#ordinary-differential-equations" style="font-size: 80%;">Ordinary Differential Equations</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs047.html#the-trial-solution" style="font-size: 80%;">The trial solution</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs006.html#minimization-process" style="font-size: 80%;">Minimization process</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs007.html#minimizing-the-cost-function-using-gradient-descent-and-automatic-differentiation" style="font-size: 80%;">Minimizing the cost function using gradient descent and automatic differentiation</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs008.html#example-exponential-decay" style="font-size: 80%;">Example: Exponential decay</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs009.html#the-function-to-solve-for" style="font-size: 80%;">The function to solve for</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs047.html#the-trial-solution" style="font-size: 80%;">The trial solution</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs011.html#setup-of-network" style="font-size: 80%;">Setup of Network</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs012.html#reformulating-the-problem" style="font-size: 80%;">Reformulating the problem</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs013.html#more-technicalities" style="font-size: 80%;">More technicalities</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs038.html#more-details" style="font-size: 80%;">More details</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs015.html#a-possible-implementation-of-a-neural-network" style="font-size: 80%;">A possible implementation of a neural network</a></li>
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||||
<!-- navigation toc: --> <li><a href="._week42-bs016.html#technicalities" style="font-size: 80%;">Technicalities</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs017.html#final-technicalities-i" style="font-size: 80%;">Final technicalities I</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs018.html#final-technicalities-ii" style="font-size: 80%;">Final technicalities II</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs019.html#final-technicalities-iii" style="font-size: 80%;">Final technicalities III</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs020.html#final-technicalities-iv" style="font-size: 80%;">Final technicalities IV</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs021.html#back-propagation" style="font-size: 80%;">Back propagation</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs022.html#gradient-descent" style="font-size: 80%;">Gradient descent</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs023.html#the-code-for-solving-the-ode" style="font-size: 80%;">The code for solving the ODE</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs024.html#the-network-with-one-input-layer-specified-number-of-hidden-layers-and-one-output-layer" style="font-size: 80%;">The network with one input layer, specified number of hidden layers, and one output layer</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs025.html#example-population-growth" style="font-size: 80%;">Example: Population growth</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs026.html#setting-up-the-problem" style="font-size: 80%;">Setting up the problem</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs047.html#the-trial-solution" style="font-size: 80%;">The trial solution</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs028.html#the-program-using-autograd" style="font-size: 80%;">The program using Autograd</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs029.html#using-forward-euler-to-solve-the-ode" style="font-size: 80%;">Using forward Euler to solve the ODE</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs030.html#example-solving-the-one-dimensional-poisson-equation" style="font-size: 80%;">Example: Solving the one dimensional Poisson equation</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs031.html#the-specific-equation-to-solve-for" style="font-size: 80%;">The specific equation to solve for</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs032.html#solving-the-equation-using-autograd" style="font-size: 80%;">Solving the equation using Autograd</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs033.html#comparing-with-a-numerical-scheme" style="font-size: 80%;">Comparing with a numerical scheme</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs034.html#setting-up-the-code" style="font-size: 80%;">Setting up the code</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs035.html#partial-differential-equations" style="font-size: 80%;">Partial Differential Equations</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs036.html#type-of-problem" style="font-size: 80%;">Type of problem</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs037.html#network-requirements" style="font-size: 80%;">Network requirements</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs038.html#more-details" style="font-size: 80%;">More details</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs039.html#example-the-diffusion-equation" style="font-size: 80%;">Example: The diffusion equation</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs040.html#defining-the-problem" style="font-size: 80%;">Defining the problem</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs041.html#setting-up-the-network-using-autograd" style="font-size: 80%;">Setting up the network using Autograd</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs042.html#setting-up-the-network-using-autograd-the-trial-solution" style="font-size: 80%;">Setting up the network using Autograd; The trial solution</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs043.html#why-the-jacobian" style="font-size: 80%;">Why the jacobian?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs044.html#setting-up-the-network-using-autograd-the-full-program" style="font-size: 80%;">Setting up the network using Autograd; The full program</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs045.html#example-solving-the-wave-equation-with-neural-networks" style="font-size: 80%;">Example: Solving the wave equation with Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs046.html#the-problem-to-solve-for" style="font-size: 80%;">The problem to solve for</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs047.html#the-trial-solution" style="font-size: 80%;">The trial solution</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs048.html#the-analytical-solution" style="font-size: 80%;">The analytical solution</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs049.html#solving-the-wave-equation-the-full-program-using-autograd" style="font-size: 80%;">Solving the wave equation - the full program using Autograd</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs050.html#resources-on-differential-equations-and-deep-learning" style="font-size: 80%;">Resources on differential equations and deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs051.html#convolutional-neural-networks-recognizing-images" style="font-size: 80%;">Convolutional Neural Networks (recognizing images)</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs052.html#neural-networks-vs-cnns" style="font-size: 80%;">Neural Networks vs CNNs</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs053.html#why-cnns-for-images-sound-files-medical-images-from-ct-scans-etc" style="font-size: 80%;">Why CNNS for images, sound files, medical images from CT scans etc?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs054.html#regular-nns-don-t-scale-well-to-full-images" style="font-size: 80%;">Regular NNs don’t scale well to full images</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs055.html#3d-volumes-of-neurons" style="font-size: 80%;">3D volumes of neurons</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs056.html#layers-used-to-build-cnns" style="font-size: 80%;">Layers used to build CNNs</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs057.html#transforming-images" style="font-size: 80%;">Transforming images</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs058.html#cnns-in-brief" style="font-size: 80%;">CNNs in brief</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs059.html#cnns-in-more-detail-building-convolutional-neural-networks-in-tensorflow-and-keras" style="font-size: 80%;">CNNs in more detail, building convolutional neural networks in Tensorflow and Keras</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs060.html#setting-it-up" style="font-size: 80%;">Setting it up</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs061.html#the-mnist-dataset-again" style="font-size: 80%;">The MNIST dataset again</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs062.html#strong-correlations" style="font-size: 80%;">Strong correlations</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs063.html#layers-of-a-cnn" style="font-size: 80%;">Layers of a CNN</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs064.html#systematic-reduction" style="font-size: 80%;">Systematic reduction</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs065.html#prerequisites-collect-and-pre-process-data" style="font-size: 80%;">Prerequisites: Collect and pre-process data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs066.html#importing-keras-and-tensorflow" style="font-size: 80%;">Importing Keras and Tensorflow</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs067.html#running-with-keras" style="font-size: 80%;">Running with Keras</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs068.html#final-part" style="font-size: 80%;">Final part</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs069.html#final-visualization" style="font-size: 80%;">Final visualization</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs070.html#the-cifar01-data-set" style="font-size: 80%;">The CIFAR01 data set</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs071.html#verifying-the-data-set" style="font-size: 80%;">Verifying the data set</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs072.html#set-up-the-model" style="font-size: 80%;">Set up the model</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs073.html#add-dense-layers-on-top" style="font-size: 80%;">Add Dense layers on top</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs074.html#compile-and-train-the-model" style="font-size: 80%;">Compile and train the model</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._week42-bs075.html#finally-evaluate-the-model" style="font-size: 80%;">Finally, evaluate the model</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
@@ -190,7 +352,7 @@ MathJax.Hub.Config({
|
||||
|
||||
|
||||
<div class="jumbotron">
|
||||
<center><h1>Week 42 Convolutional (CNN) and Recurrent (RNN) Neural Networks</h1></center> <!-- document title -->
|
||||
<center><h1>Week 42 Solving differential equations and Convolutional (CNN)</h1></center> <!-- document title -->
|
||||
|
||||
<p>
|
||||
<!-- author(s): Morten Hjorth-Jensen -->
|
||||
@@ -206,7 +368,7 @@ MathJax.Hub.Config({
|
||||
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
|
||||
<br>
|
||||
<p>
|
||||
<center><h4>Oct 17, 2020</h4></center> <!-- date -->
|
||||
<center><h4>Oct 19, 2021</h4></center> <!-- date -->
|
||||
<br>
|
||||
<p>
|
||||
|
||||
@@ -230,7 +392,7 @@ MathJax.Hub.Config({
|
||||
<li><a href="._week42-bs008.html">9</a></li>
|
||||
<li><a href="._week42-bs009.html">10</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._week42-bs034.html">35</a></li>
|
||||
<li><a href="._week42-bs075.html">76</a></li>
|
||||
<li><a href="._week42-bs001.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
@@ -242,13 +404,13 @@ MathJax.Hub.Config({
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
<a href="https://..."><img width="250" align=right src="https://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright --> © 1999-2020, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
|
||||
<!-- copyright --> © 1999-2021, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
|
||||
</center>
|
||||
|
||||
|
||||
|
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|
||||
collected all required additional files in ipynb-chapter9-src.tar.gz which must be distributed with the notebook
|
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||||
!split
|
||||
===== Plan for week 42 =====
|
||||
|
||||
* Thursday: Convolutional Neural Networks and examples. "Video of Lecture":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober15.mp4?vrtx=view-as-webpage"
|
||||
* Friday: Recurrent Neural Networks. "Video of Lecture":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h20/forelesningsvideoer/LectureOctober16.mp4?vrtx=view-as-webpage"
|
||||
* Thursday: Solving differential equations with Neural Networks and start Convolutional Neural Networks and examples.
|
||||
* Friday: Convolutional Neural Networks.
|
||||
|
||||
Reading suggestions for both days: "Aurelien Geron's chapters 13 and 14":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf". Autoencoders are discussed in chapter 15 of Geron's text.
|
||||
|
||||
See also the "handwritten notes from October 15":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/NotesOctober15.pdf" and "October 16":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/NotesOctober15.pdf".
|
||||
Reading suggestions for both days: "Aurelien Geron's chapters 13 and 14":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf".
|
||||
|
||||
|
||||
!bblock Excellent lectures on CNNs and RNNs
|
||||
Reference in New Issue
Block a user