diff --git a/doc/web/course.do.txt b/doc/web/course.do.txt index 7b1f68b6a..dba3f80d7 100644 --- a/doc/web/course.do.txt +++ b/doc/web/course.do.txt @@ -222,9 +222,9 @@ Acronyms for textbooks and references to chapter |----------------------------------------------------------------------------------------------------------------------------| | 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 35 | Regression analysis | Exercises TBD | HTF chapter 3 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 36 | Regression analysis and nearest neighbors| Exercises TBD | HTF chapters 3, 4 and 13 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| |----------------------------------------------------------------------------------------------------------------------------| diff --git a/doc/web/course.html b/doc/web/course.html index e26218106..b4d085602 100644 --- a/doc/web/course.html +++ b/doc/web/course.html @@ -714,24 +714,24 @@ Acronyms for textbooks and references to chapter - + - - - - - - - - - - - - - - - + + + + + + + + + + + + + + +
Week and days Topics to be covered Projects, exercises 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 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
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 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 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 index 32ad18a6d..772a2e368 100644 --- a/doc/web/schedule.do.txt +++ b/doc/web/schedule.do.txt @@ -28,9 +28,9 @@ Lectures are Thursday and Fridays 1215pm-2pm. The computer lab is (projects and |----------------------------------------------------------------------------------------------------------------------------| | 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 35 | Regression analysis | Exercises TBD | HTF chapter 3 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 36 | Regression analysis and nearest neighbors| Exercises TBD | HTF chapters 3, 4 and 13 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| |----------------------------------------------------------------------------------------------------------------------------| diff --git a/doc/web/schedule.html b/doc/web/schedule.html index 9e721dfc3..ce76f077c 100644 --- a/doc/web/schedule.html +++ b/doc/web/schedule.html @@ -93,24 +93,24 @@ Lectures are Thursday and Fridays 1215pm-2pm. The computer lab is (projects and - + - - - - - - - - - - - - - - - + + + + + + + + + + + + + + +
Week Topics to be covered Projects, exercises and deadlines Reading assignments Lab activities
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
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 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 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