Schedule and topics in more detail
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mhjensen
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@@ -184,7 +184,14 @@ The following topics will be covered
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All the above topics will be supported by examples, hands-on exercises and project work.
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===== "Possible textbooks":"https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks" =====
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===== Recommended textbooks =====
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* "Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570"
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* "Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly":"http://shop.oreilly.com/product/0636920052289.do"
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===== "Other textbooks":"https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks" =====
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_General learning book on statistical analysis_:
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@@ -207,39 +214,39 @@ _General Machine Learning Books_:
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===== Teaching schedule Fall 2018 =====
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Acronyms for textbooks and references to chapter
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* Hastie
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* Geron
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* HTF: "Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570"
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* AG: "Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly":"http://shop.oreilly.com/product/0636920052289.do"
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week and days | Topics to be covered | Projects, exercises and deadlines | Reading assignments| Lab activities |
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| Week 34| Introduction and regression analysis | Exercises | | Introduction to Git, GitHub and Python software |
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| Week 34| Introduction and regression analysis | Exercises TBD | HTF chapters 1-3 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html"| No lab first week |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 35 | Regression analysis | Exercises | | Python technicalities and work on exercises|
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| Week 35 | Regression analysis | Exercises TBD | HTF chapter 3 and and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html"| Introduction to Git, GitHub and Python software, Python technicalities and work on exercises|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 36 | Regression analysis and nearest neighbors| Exercises | | |
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| Week 36 | Regression analysis and nearest neighbors| Exercises TBD | HTF chapters 3, 4 and 13 and and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" | Work on exercises|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 37 | Classification and logistic regression | Presentation of Project 1 | | Work on project 1|
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| Week 37 | Classification and logistic regression | "Presentation of Project 1, deadline October 1":"https://compphysics.github.io/MachineLearning/doc/Projects/2018/Project1/html/Project1-bs.html" | HTF chapter 4 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" | Work on project 1|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 38 | Optimization methods | | | Work on project 1|
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| Week 38 | Optimization methods | Exercises and project 1 | HTF chapter 5 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Splines/html/Splines-bs.html" | Work on project 1, deadline October 1|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 39 | Statistics, Bayesian statistics | | | Work on Project 1|
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| Week 39 | Statistics, Bayesian statistics | Project 1 | "Lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Bayesian/html/Bayesian-bs.html" | Work on Project 1|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 40 | Statistics, Monte Carlo and Randow walks | | | |
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| Week 40 | Statistics, Monte Carlo and Randow walks | Presentation of project 2, deadline November 5 | "Lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-bs.html" | Deadline project 1, October 1|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 41 | Statistics, Monte Carlo, Gibbs and Metropolis sampling | | | |
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| Week 41 | Statistics, Monte Carlo, Gibbs and Metropolis sampling | Project 2 | "Lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-bs.html" | Work on project 2 |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 42 | Neural networks | | | |
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| Week 42 | Neural networks | Project 2 | HTF chapter 11 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" | Work on project 2 |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 43 | Neural networks | | | |
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| Week 43 | Neural networks | Project 2 | HTF chapter 11 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" | Work on project 2 |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 44 | Neural networks | | | |
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| Week 44 | Neural networks | Project 2 | HTF chapter 11 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" | Work on project 2 |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 45 | Support Vector Machines | | | |
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| Week 45 | Support Vector Machines | Presentation and discussion of project 3 | HTF chapter 12 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/svm/html/svm-bs.html" | Deadline project 2 November 5 |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 46 | Decision trees | | | |
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| Week 46 | Decision trees | Project 3 | HTF chapter 9 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/DecisionTrees/html/DecisionTrees-bs.html" | Work on project 3 |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 47 | Unsupervised learning, Boltzmann machines | | | |
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| Week 47 | Unsupervised learning, Boltzmann machines | Project 3 | HTF chapter 14 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/BM/html/BM-bs.html" | Work on project 3 |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 48 | Unsupervised learning and summary of course | | | |
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| Week 48 | Unsupervised learning, summary of course and final workshop | Project 3 | Lecture notes | Final workshop with presentation of project 3 |
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|----------------------------------------------------------------------------------------------------------------------------|
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+31
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@@ -106,12 +106,13 @@ div { text-align: justify; text-justify: inter-word; }
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None,
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'___sec21'),
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('Machine learning', 3, None, '___sec22'),
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('"Possible '
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('Recommended textbooks', 2, None, '___sec23'),
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('"Other '
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'textbooks":"https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks"',
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2,
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None,
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'___sec23'),
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('Teaching schedule Fall 2018', 2, None, '___sec24')]}
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'___sec24'),
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('Teaching schedule Fall 2018', 2, None, '___sec25')]}
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end of tocinfo -->
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<body>
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@@ -672,7 +673,14 @@ The following topics will be covered
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All the above topics will be supported by examples, hands-on exercises and project work.
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<h2 id="___sec23"><a href="https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks" target="_self">Possible textbooks</a> </h2>
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<h2 id="___sec23">Recommended textbooks </h2>
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<ul>
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<li> <a href="https://www.springer.com/gp/book/9780387848570" target="_self">Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer</a></li>
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<li> <a href="http://shop.oreilly.com/product/0636920052289.do" target="_self">Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly</a></li>
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</ul>
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<h2 id="___sec24"><a href="https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks" target="_self">Other textbooks</a> </h2>
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<p>
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<b>General learning book on statistical analysis</b>:
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@@ -694,36 +702,36 @@ All the above topics will be supported by examples, hands-on exercises and proje
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<!-- !split -->
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<h2 id="___sec24">Teaching schedule Fall 2018 </h2>
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<h2 id="___sec25">Teaching schedule Fall 2018 </h2>
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<p>
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Acronyms for textbooks and references to chapter
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<ul>
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<li> Hastie</li>
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<li> Geron</li>
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<li> HTF: <a href="https://www.springer.com/gp/book/9780387848570" target="_self">Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer</a></li>
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<li> AG: <a href="http://shop.oreilly.com/product/0636920052289.do" target="_self">Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly</a></li>
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</ul>
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<table border="1">
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<thead>
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<tr><th align="center">Week and days</th> <th align="center"> Topics to be covered </th> <th align="center">Projects and deadlines</th> <th align="center">Reading assignments</th> <th align="center">Lab activities</th> </tr>
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<tr><th align="center">Week and days</th> <th align="center"> Topics to be covered </th> <th align="center"> Projects, exercises and deadlines </th> <th align="center"> Reading assignments </th> <th align="center"> Lab activities </th> </tr>
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</thead>
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<tbody>
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<tr><td align="center"> Week 34 </td> <td align="center"> Introduction and regression analysis </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 35 </td> <td align="center"> Regression analysis </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 36 </td> <td align="center"> Regression analysis and nearest neighbors </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 37 </td> <td align="center"> Classification and logistic regression </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 38 </td> <td align="center"> Optimization methods </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 39 </td> <td align="center"> Statistics, Bayesian statistics </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 40 </td> <td align="center"> Statistics, Monte Carlo and Randow walks </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 41 </td> <td align="center"> Statistics, Monte Carlo, Gibbs and Metropolis sampling </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 42 </td> <td align="center"> Neural networks </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 43 </td> <td align="center"> Neural networks </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 44 </td> <td align="center"> Neural networks </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 45 </td> <td align="center"> Support Vector Machines </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 46 </td> <td align="center"> Decision trees </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 47 </td> <td align="center"> Unsupervised learning, Boltzmann machines </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 48 </td> <td align="center"> Unsupervised learning and summary of course </td> <td align="center"> </td> <td align="center"> </td> <td align="center"> </td> </tr>
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<tr><td align="center"> Week 34 </td> <td align="center"> Introduction and regression analysis </td> <td align="center"> Exercises TBD </td> <td align="center"> HTF chapters 1-3 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" target="_self">lecture notes</a> </td> <td align="center"> No lab first week </td> </tr>
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<tr><td align="center"> Week 35 </td> <td align="center"> Regression analysis </td> <td align="center"> Exercises TBD </td> <td align="center"> HTF chapter 3 and and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Introduction to Git, GitHub and Python software, Python technicalities and work on exercises </td> </tr>
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<tr><td align="center"> Week 36 </td> <td align="center"> Regression analysis and nearest neighbors </td> <td align="center"> Exercises TBD </td> <td align="center"> HTF chapters 3, 4 and 13 and and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on exercises </td> </tr>
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<tr><td align="center"> Week 37 </td> <td align="center"> Classification and logistic regression </td> <td align="center"> <a href="https://compphysics.github.io/MachineLearning/doc/Projects/2018/Project1/html/Project1-bs.html" target="_self">Presentation of Project 1, deadline October 1</a> </td> <td align="center"> HTF chapter 4 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 1 </td> </tr>
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<tr><td align="center"> Week 38 </td> <td align="center"> Optimization methods </td> <td align="center"> Exercises and project 1 </td> <td align="center"> HTF chapter 5 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Splines/html/Splines-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 1, deadline October 1 </td> </tr>
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<tr><td align="center"> Week 39 </td> <td align="center"> Statistics, Bayesian statistics </td> <td align="center"> Project 1 </td> <td align="center"> <a href="https://compphysics.github.io/MachineLearning/doc/pub/Bayesian/html/Bayesian-bs.html" target="_self">Lecture notes</a> </td> <td align="center"> Work on Project 1 </td> </tr>
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<tr><td align="center"> Week 40 </td> <td align="center"> Statistics, Monte Carlo and Randow walks </td> <td align="center"> Presentation of project 2, deadline November 5 </td> <td align="center"> <a href="https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-bs.html" target="_self">Lecture notes</a> </td> <td align="center"> Deadline project 1, October 1 </td> </tr>
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<tr><td align="center"> Week 41 </td> <td align="center"> Statistics, Monte Carlo, Gibbs and Metropolis sampling </td> <td align="center"> Project 2 </td> <td align="center"> <a href="https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-bs.html" target="_self">Lecture notes</a> </td> <td align="center"> Work on project 2 </td> </tr>
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<tr><td align="center"> Week 42 </td> <td align="center"> Neural networks </td> <td align="center"> Project 2 </td> <td align="center"> HTF chapter 11 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 2 </td> </tr>
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<tr><td align="center"> Week 43 </td> <td align="center"> Neural networks </td> <td align="center"> Project 2 </td> <td align="center"> HTF chapter 11 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 2 </td> </tr>
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<tr><td align="center"> Week 44 </td> <td align="center"> Neural networks </td> <td align="center"> Project 2 </td> <td align="center"> HTF chapter 11 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 2 </td> </tr>
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<tr><td align="center"> Week 45 </td> <td align="center"> Support Vector Machines </td> <td align="center"> Presentation and discussion of project 3 </td> <td align="center"> HTF chapter 12 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/svm/html/svm-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Deadline project 2 November 5 </td> </tr>
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<tr><td align="center"> Week 46 </td> <td align="center"> Decision trees </td> <td align="center"> Project 3 </td> <td align="center"> HTF chapter 9 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/DecisionTrees/html/DecisionTrees-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 3 </td> </tr>
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<tr><td align="center"> Week 47 </td> <td align="center"> Unsupervised learning, Boltzmann machines </td> <td align="center"> Project 3 </td> <td align="center"> HTF chapter 14 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/BM/html/BM-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 3 </td> </tr>
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<tr><td align="center"> Week 48 </td> <td align="center"> Unsupervised learning, summary of course and final workshop </td> <td align="center"> Project 3 </td> <td align="center"> Lecture notes </td> <td align="center"> Final workshop with presentation of project 3 </td> </tr>
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</tbody>
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</table>
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@@ -0,0 +1,58 @@
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# Strange way of testing for vortex...
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# #ifdef NON_VORTEX
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TITLE: Overview of course material: Computational Physics
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TOC: off
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# #else
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TITLE: Tentative schedule for FYS-STK3155/4155
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AUTHOR: "Morten Hjorth-Jensen":"http://mhjgit.github.io/info/doc/web/" at Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University, USA & Department of Physics, University of Oslo, Norway
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# #endif
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!split
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===== Teaching schedule Fall 2018 =====
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Acronyms for textbooks and references to chapter
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* HTF: "Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570"
|
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* AG: "Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly":"http://shop.oreilly.com/product/0636920052289.do"
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Lectures are Thursday and Fridays 1215pm-2pm. The computer lab is (projects and exercises) is on Wednesdays. Depending on how many people register for the course, we may set up four lab groups as follows
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* Group 1: Wednesdays 10am-12pm
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* Group 2: Wednesdays 12pm-2pm
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* Group 3: Wednesdays 2pm-4pm
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* Group 4: Wednesdays 4pm-6pm
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week | Topics to be covered | Projects, exercises and deadlines | Reading assignments| Lab activities |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 34| Introduction and regression analysis | Exercises TBD | HTF chapters 1-3 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html"| No lab first week |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 35 | Regression analysis | Exercises TBD | HTF chapter 3 and and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html"| Introduction to Git, GitHub and Python software, Python technicalities and work on exercises|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 36 | Regression analysis and nearest neighbors| Exercises TBD | HTF chapters 3, 4 and 13 and and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" | Work on exercises|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 37 | Classification and logistic regression | "Presentation of Project 1, deadline October 1":"https://compphysics.github.io/MachineLearning/doc/Projects/2018/Project1/html/Project1-bs.html" | HTF chapter 4 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" | Work on project 1|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 38 | Optimization methods | Exercises and project 1 | HTF chapter 5 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Splines/html/Splines-bs.html" | Work on project 1, deadline October 1|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 39 | Statistics, Bayesian statistics | Project 1 | "Lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Bayesian/html/Bayesian-bs.html" | Work on Project 1|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 40 | Statistics, Monte Carlo and Randow walks | Presentation of project 2, deadline November 5 | "Lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-bs.html" | Deadline project 1, October 1|
|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 41 | Statistics, Monte Carlo, Gibbs and Metropolis sampling | Project 2 | "Lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-bs.html" | Work on project 2 |
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 42 | Neural networks | Project 2 | HTF chapter 11 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" | Work on project 2 |
|
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|----------------------------------------------------------------------------------------------------------------------------|
|
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| Week 43 | Neural networks | Project 2 | HTF chapter 11 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" | Work on project 2 |
|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 44 | Neural networks | Project 2 | HTF chapter 11 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" | Work on project 2 |
|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 45 | Support Vector Machines | Presentation and discussion of project 3 | HTF chapter 12 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/svm/html/svm-bs.html" | Deadline project 2 November 5 |
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|----------------------------------------------------------------------------------------------------------------------------|
|
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| Week 46 | Decision trees | Project 3 | HTF chapter 9 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/DecisionTrees/html/DecisionTrees-bs.html" | Work on project 3 |
|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 47 | Unsupervised learning, Boltzmann machines | Project 3 | HTF chapter 14 and "lecture notes":"https://compphysics.github.io/MachineLearning/doc/pub/BM/html/BM-bs.html" | Work on project 3 |
|
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|----------------------------------------------------------------------------------------------------------------------------|
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| Week 48 | Unsupervised learning, summary of course and final workshop | Project 3 | Lecture notes | Final workshop with presentation of project 3 |
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|----------------------------------------------------------------------------------------------------------------------------|
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<!-- author(s): <a href="http://mhjgit.github.io/info/doc/web/" target="_self">Morten Hjorth-Jensen</a> -->
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<b><a href="http://mhjgit.github.io/info/doc/web/" target="_self">Morten Hjorth-Jensen</a></b> [1, 2]
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<!-- institution(s) -->
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<center>[1] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University, USA</b></center>
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<center>[2] <b>Department of Physics, University of Oslo, Norway</b></center>
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<h2 id="___sec0">Teaching schedule Fall 2018 </h2>
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Acronyms for textbooks and references to chapter
|
||||
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||||
<ul>
|
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<li> HTF: <a href="https://www.springer.com/gp/book/9780387848570" target="_self">Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer</a></li>
|
||||
<li> AG: <a href="http://shop.oreilly.com/product/0636920052289.do" target="_self">Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly</a></li>
|
||||
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|
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||||
Lectures are Thursday and Fridays 1215pm-2pm. The computer lab is (projects and exercises) is on Wednesdays. Depending on how many people register for the course, we may set up four lab groups as follows
|
||||
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||||
<ul>
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||||
<li> Group 1: Wednesdays 10am-12pm</li>
|
||||
<li> Group 2: Wednesdays 12pm-2pm</li>
|
||||
<li> Group 3: Wednesdays 2pm-4pm</li>
|
||||
<li> Group 4: Wednesdays 4pm-6pm</li>
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<tr><th align="center"> Week </th> <th align="center"> Topics to be covered </th> <th align="center"> Projects, exercises and deadlines </th> <th align="center"> Reading assignments </th> <th align="center"> Lab activities </th> </tr>
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<tbody>
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<tr><td align="center"> Week 34 </td> <td align="center"> Introduction and regression analysis </td> <td align="center"> Exercises TBD </td> <td align="center"> HTF chapters 1-3 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" target="_self">lecture notes</a> </td> <td align="center"> No lab first week </td> </tr>
|
||||
<tr><td align="center"> Week 35 </td> <td align="center"> Regression analysis </td> <td align="center"> Exercises TBD </td> <td align="center"> HTF chapter 3 and and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Introduction to Git, GitHub and Python software, Python technicalities and work on exercises </td> </tr>
|
||||
<tr><td align="center"> Week 36 </td> <td align="center"> Regression analysis and nearest neighbors </td> <td align="center"> Exercises TBD </td> <td align="center"> HTF chapters 3, 4 and 13 and and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on exercises </td> </tr>
|
||||
<tr><td align="center"> Week 37 </td> <td align="center"> Classification and logistic regression </td> <td align="center"> <a href="https://compphysics.github.io/MachineLearning/doc/Projects/2018/Project1/html/Project1-bs.html" target="_self">Presentation of Project 1, deadline October 1</a> </td> <td align="center"> HTF chapter 4 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 1 </td> </tr>
|
||||
<tr><td align="center"> Week 38 </td> <td align="center"> Optimization methods </td> <td align="center"> Exercises and project 1 </td> <td align="center"> HTF chapter 5 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/Splines/html/Splines-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 1, deadline October 1 </td> </tr>
|
||||
<tr><td align="center"> Week 39 </td> <td align="center"> Statistics, Bayesian statistics </td> <td align="center"> Project 1 </td> <td align="center"> <a href="https://compphysics.github.io/MachineLearning/doc/pub/Bayesian/html/Bayesian-bs.html" target="_self">Lecture notes</a> </td> <td align="center"> Work on Project 1 </td> </tr>
|
||||
<tr><td align="center"> Week 40 </td> <td align="center"> Statistics, Monte Carlo and Randow walks </td> <td align="center"> Presentation of project 2, deadline November 5 </td> <td align="center"> <a href="https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-bs.html" target="_self">Lecture notes</a> </td> <td align="center"> Deadline project 1, October 1 </td> </tr>
|
||||
<tr><td align="center"> Week 41 </td> <td align="center"> Statistics, Monte Carlo, Gibbs and Metropolis sampling </td> <td align="center"> Project 2 </td> <td align="center"> <a href="https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-bs.html" target="_self">Lecture notes</a> </td> <td align="center"> Work on project 2 </td> </tr>
|
||||
<tr><td align="center"> Week 42 </td> <td align="center"> Neural networks </td> <td align="center"> Project 2 </td> <td align="center"> HTF chapter 11 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 2 </td> </tr>
|
||||
<tr><td align="center"> Week 43 </td> <td align="center"> Neural networks </td> <td align="center"> Project 2 </td> <td align="center"> HTF chapter 11 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 2 </td> </tr>
|
||||
<tr><td align="center"> Week 44 </td> <td align="center"> Neural networks </td> <td align="center"> Project 2 </td> <td align="center"> HTF chapter 11 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 2 </td> </tr>
|
||||
<tr><td align="center"> Week 45 </td> <td align="center"> Support Vector Machines </td> <td align="center"> Presentation and discussion of project 3 </td> <td align="center"> HTF chapter 12 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/svm/html/svm-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Deadline project 2 November 5 </td> </tr>
|
||||
<tr><td align="center"> Week 46 </td> <td align="center"> Decision trees </td> <td align="center"> Project 3 </td> <td align="center"> HTF chapter 9 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/DecisionTrees/html/DecisionTrees-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 3 </td> </tr>
|
||||
<tr><td align="center"> Week 47 </td> <td align="center"> Unsupervised learning, Boltzmann machines </td> <td align="center"> Project 3 </td> <td align="center"> HTF chapter 14 and <a href="https://compphysics.github.io/MachineLearning/doc/pub/BM/html/BM-bs.html" target="_self">lecture notes</a> </td> <td align="center"> Work on project 3 </td> </tr>
|
||||
<tr><td align="center"> Week 48 </td> <td align="center"> Unsupervised learning, summary of course and final workshop </td> <td align="center"> Project 3 </td> <td align="center"> Lecture notes </td> <td align="center"> Final workshop with presentation of project 3 </td> </tr>
|
||||
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||||
Reference in New Issue
Block a user