diff --git a/doc/web/course.do.txt b/doc/web/course.do.txt index 407a42f88..7b1f68b6a 100644 --- a/doc/web/course.do.txt +++ b/doc/web/course.do.txt @@ -184,7 +184,14 @@ The following topics will be covered All the above topics will be supported by examples, hands-on exercises and project work. -===== "Possible textbooks":"https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks" ===== +===== Recommended textbooks ===== + +* "Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570" + +* "Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly":"http://shop.oreilly.com/product/0636920052289.do" + + +===== "Other textbooks":"https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks" ===== _General learning book on statistical analysis_: @@ -207,39 +214,39 @@ _General Machine Learning Books_: ===== Teaching schedule Fall 2018 ===== Acronyms for textbooks and references to chapter -* Hastie -* Geron +* HTF: "Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570" +* AG: "Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly":"http://shop.oreilly.com/product/0636920052289.do" |----------------------------------------------------------------------------------------------------------------------------| | Week and days | Topics to be covered | Projects, exercises and deadlines | Reading assignments| Lab activities | |----------------------------------------------------------------------------------------------------------------------------| -| Week 34| Introduction and regression analysis | Exercises | | Introduction to Git, GitHub and Python software | +| 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 | |----------------------------------------------------------------------------------------------------------------------------| -| Week 35 | Regression analysis | Exercises | | Python technicalities and work on exercises| +| 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| |----------------------------------------------------------------------------------------------------------------------------| -| Week 36 | Regression analysis and nearest neighbors| Exercises | | | +| 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| |----------------------------------------------------------------------------------------------------------------------------| -| Week 37 | Classification and logistic regression | Presentation of Project 1 | | Work on project 1| +| 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| |----------------------------------------------------------------------------------------------------------------------------| -| Week 38 | Optimization methods | | | Work on project 1| +| 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| |----------------------------------------------------------------------------------------------------------------------------| -| Week 39 | Statistics, Bayesian statistics | | | Work on Project 1| +| 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| |----------------------------------------------------------------------------------------------------------------------------| -| Week 40 | Statistics, Monte Carlo and Randow walks | | | | +| 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| |----------------------------------------------------------------------------------------------------------------------------| -| Week 41 | Statistics, Monte Carlo, Gibbs and Metropolis sampling | | | | +| 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 | |----------------------------------------------------------------------------------------------------------------------------| -| Week 42 | Neural networks | | | | +| 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 | |----------------------------------------------------------------------------------------------------------------------------| -| Week 43 | Neural networks | | | | +| 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 | |----------------------------------------------------------------------------------------------------------------------------| -| Week 44 | Neural networks | | | | +| 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 | |----------------------------------------------------------------------------------------------------------------------------| -| Week 45 | Support Vector Machines | | | | +| 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 | |----------------------------------------------------------------------------------------------------------------------------| -| Week 46 | Decision trees | | | | +| 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 | |----------------------------------------------------------------------------------------------------------------------------| -| Week 47 | Unsupervised learning, Boltzmann machines | | | | +| 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 | |----------------------------------------------------------------------------------------------------------------------------| -| Week 48 | Unsupervised learning and summary of course | | | | +| Week 48 | Unsupervised learning, summary of course and final workshop | Project 3 | Lecture notes | Final workshop with presentation of project 3 | |----------------------------------------------------------------------------------------------------------------------------| diff --git a/doc/web/course.html b/doc/web/course.html index e85274b41..e26218106 100644 --- a/doc/web/course.html +++ b/doc/web/course.html @@ -106,12 +106,13 @@ div { text-align: justify; text-justify: inter-word; } None, '___sec21'), ('Machine learning', 3, None, '___sec22'), - ('"Possible ' + ('Recommended textbooks', 2, None, '___sec23'), + ('"Other ' 'textbooks":"https://github.com/CompPhysics/MachineLearning/tree/master/doc/Textbooks"', 2, None, - '___sec23'), - ('Teaching schedule Fall 2018', 2, None, '___sec24')]} + '___sec24'), + ('Teaching schedule Fall 2018', 2, None, '___sec25')]} end of tocinfo --> @@ -672,7 +673,14 @@ The following topics will be covered All the above topics will be supported by examples, hands-on exercises and project work. -

Possible textbooks

+

Recommended textbooks

+ + + +

Other textbooks

General learning book on statistical analysis: @@ -694,36 +702,36 @@ All the above topics will be supported by examples, hands-on exercises and proje -

Teaching schedule Fall 2018

+

Teaching schedule Fall 2018

Acronyms for textbooks and references to chapter

- + - - - - - - - - - - - - - - - + + + + + + + + + + + + + + +
Week and days Topics to be covered Projects and deadlines Reading assignments Lab activities
Week and days Topics to be covered Projects, exercises and deadlines Reading assignments Lab activities
Week 34 Introduction and regression analysis
Week 35 Regression analysis
Week 36 Regression analysis and nearest neighbors
Week 37 Classification and logistic regression
Week 38 Optimization methods
Week 39 Statistics, Bayesian statistics
Week 40 Statistics, Monte Carlo and Randow walks
Week 41 Statistics, Monte Carlo, Gibbs and Metropolis sampling
Week 42 Neural networks
Week 43 Neural networks
Week 44 Neural networks
Week 45 Support Vector Machines
Week 46 Decision trees
Week 47 Unsupervised learning, Boltzmann machines
Week 48 Unsupervised learning and summary of course
Week 34 Introduction and regression analysis Exercises TBD HTF chapters 1-3 and lecture notes No lab first week
Week 35 Regression analysis Exercises TBD HTF chapter 3 and and lecture notes Introduction to Git, GitHub and Python software, Python technicalities and work on exercises
Week 36 Regression analysis and nearest neighbors Exercises TBD HTF chapters 3, 4 and 13 and and lecture notes Work on exercises
Week 37 Classification and logistic regression Presentation of Project 1, deadline October 1 HTF chapter 4 and lecture notes Work on project 1
Week 38 Optimization methods Exercises and project 1 HTF chapter 5 and lecture notes Work on project 1, deadline October 1
Week 39 Statistics, Bayesian statistics Project 1 Lecture notes Work on Project 1
Week 40 Statistics, Monte Carlo and Randow walks Presentation of project 2, deadline November 5 Lecture notes Deadline project 1, October 1
Week 41 Statistics, Monte Carlo, Gibbs and Metropolis sampling Project 2 Lecture notes Work on project 2
Week 42 Neural networks Project 2 HTF chapter 11 and lecture notes Work on project 2
Week 43 Neural networks Project 2 HTF chapter 11 and lecture notes Work on project 2
Week 44 Neural networks Project 2 HTF chapter 11 and lecture notes Work on project 2
Week 45 Support Vector Machines Presentation and discussion of project 3 HTF chapter 12 and lecture notes Deadline project 2 November 5
Week 46 Decision trees Project 3 HTF chapter 9 and lecture notes Work on project 3
Week 47 Unsupervised learning, Boltzmann machines Project 3 HTF chapter 14 and lecture notes Work on project 3
Week 48 Unsupervised learning, summary of course and final workshop Project 3 Lecture notes Final workshop with presentation of project 3
diff --git a/doc/web/schedule.do.txt b/doc/web/schedule.do.txt new file mode 100644 index 000000000..32ad18a6d --- /dev/null +++ b/doc/web/schedule.do.txt @@ -0,0 +1,58 @@ +# Strange way of testing for vortex... +# #ifdef NON_VORTEX +TITLE: Overview of course material: Computational Physics + +TOC: off +# #else +TITLE: Tentative schedule for FYS-STK3155/4155 +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 +# #endif + + + +!split +===== Teaching schedule Fall 2018 ===== + +Acronyms for textbooks and references to chapter +* HTF: "Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570" +* AG: "Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly":"http://shop.oreilly.com/product/0636920052289.do" + +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 +* Group 1: Wednesdays 10am-12pm +* Group 2: Wednesdays 12pm-2pm +* Group 3: Wednesdays 2pm-4pm +* Group 4: Wednesdays 4pm-6pm + +|----------------------------------------------------------------------------------------------------------------------------| +| Week | Topics to be covered | Projects, exercises and deadlines | Reading assignments| Lab activities | +|----------------------------------------------------------------------------------------------------------------------------| +| 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 | +|----------------------------------------------------------------------------------------------------------------------------| +| 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| +|----------------------------------------------------------------------------------------------------------------------------| +| 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| +|----------------------------------------------------------------------------------------------------------------------------| +| 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| +|----------------------------------------------------------------------------------------------------------------------------| +| 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| +|----------------------------------------------------------------------------------------------------------------------------| +| 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| +|----------------------------------------------------------------------------------------------------------------------------| +| 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| +|----------------------------------------------------------------------------------------------------------------------------| +| 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 | +|----------------------------------------------------------------------------------------------------------------------------| +| 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 | +|----------------------------------------------------------------------------------------------------------------------------| +| 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 | +|----------------------------------------------------------------------------------------------------------------------------| +| 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 | +|----------------------------------------------------------------------------------------------------------------------------| +| 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 | +|----------------------------------------------------------------------------------------------------------------------------| +| 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 | +|----------------------------------------------------------------------------------------------------------------------------| +| 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 | +|----------------------------------------------------------------------------------------------------------------------------| +| Week 48 | Unsupervised learning, summary of course and final workshop | Project 3 | Lecture notes | Final workshop with presentation of project 3 | +|----------------------------------------------------------------------------------------------------------------------------| diff --git a/doc/web/schedule.html b/doc/web/schedule.html new file mode 100644 index 000000000..9e721dfc3 --- /dev/null +++ b/doc/web/schedule.html @@ -0,0 +1,123 @@ + + + + + + + +Tentative schedule for FYS-STK3155/4155 + + + + + + + + + + + + + + + + + +

Tentative schedule for FYS-STK3155/4155

+ +

+ + +

+Morten Hjorth-Jensen [1, 2] +
+ +

+ + +

[1] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University, USA
+
[2] Department of Physics, University of Oslo, Norway
+
+ +

+ + +

Teaching schedule Fall 2018

+ +

+Acronyms for textbooks and references to chapter + +

+ +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 + + + + + + + + + + + + + + + + + + + + + + + + +
Week Topics to be covered Projects, exercises and deadlines Reading assignments Lab activities
Week 34 Introduction and regression analysis Exercises TBD HTF chapters 1-3 and lecture notes No lab first week
Week 35 Regression analysis Exercises TBD HTF chapter 3 and and lecture notes Introduction to Git, GitHub and Python software, Python technicalities and work on exercises
Week 36 Regression analysis and nearest neighbors Exercises TBD HTF chapters 3, 4 and 13 and and lecture notes Work on exercises
Week 37 Classification and logistic regression Presentation of Project 1, deadline October 1 HTF chapter 4 and lecture notes Work on project 1
Week 38 Optimization methods Exercises and project 1 HTF chapter 5 and lecture notes Work on project 1, deadline October 1
Week 39 Statistics, Bayesian statistics Project 1 Lecture notes Work on Project 1
Week 40 Statistics, Monte Carlo and Randow walks Presentation of project 2, deadline November 5 Lecture notes Deadline project 1, October 1
Week 41 Statistics, Monte Carlo, Gibbs and Metropolis sampling Project 2 Lecture notes Work on project 2
Week 42 Neural networks Project 2 HTF chapter 11 and lecture notes Work on project 2
Week 43 Neural networks Project 2 HTF chapter 11 and lecture notes Work on project 2
Week 44 Neural networks Project 2 HTF chapter 11 and lecture notes Work on project 2
Week 45 Support Vector Machines Presentation and discussion of project 3 HTF chapter 12 and lecture notes Deadline project 2 November 5
Week 46 Decision trees Project 3 HTF chapter 9 and lecture notes Work on project 3
Week 47 Unsupervised learning, Boltzmann machines Project 3 HTF chapter 14 and lecture notes Work on project 3
Week 48 Unsupervised learning, summary of course and final workshop Project 3 Lecture notes Final workshop with presentation of project 3
+ + + + + + + +