added video
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@@ -311,6 +311,11 @@ MathJax.Hub.Config({
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<ul>
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<li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks.</li>
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<ul>
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<li> <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage" target="_self">Video of Lecture</a></li>
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</ul>
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<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
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</ul>
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@@ -163,6 +163,11 @@ MathJax.Hub.Config({
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<ul>
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<p><li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks.</li>
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<ul>
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<p><li> <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture</a></li>
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</ul>
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<p><li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
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</ul>
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<p>
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@@ -263,6 +263,11 @@ MathJax.Hub.Config({
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<ul>
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<li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks.</li>
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<ul>
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<li> <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture</a></li>
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</ul>
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<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
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</ul>
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@@ -268,6 +268,11 @@ MathJax.Hub.Config({
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<ul>
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<li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks.</li>
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<ul>
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<li> <a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage" target="_blank">Video of Lecture</a></li>
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</ul>
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<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
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</ul>
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@@ -7,6 +7,7 @@ DATE: today
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===== Plan for week 40 =====
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* Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks.
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* "Video of Lecture":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage"
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* Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.
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Reading suggestions for both days: "Aurelien Geron's chapter 10":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" and Hastie et al chapter 11.
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