From 602b1c6ee00a9288b29f7d806aee48b61c2d327c Mon Sep 17 00:00:00 2001 From: Morten Hjorth-Jensen Date: Tue, 23 Aug 2022 11:14:28 +0200 Subject: [PATCH] update --- doc/LectureNotes/schedule.md | 87 ++++++++++++++++++------------------ doc/LectureNotes/teachers.md | 14 +++--- 2 files changed, 50 insertions(+), 51 deletions(-) diff --git a/doc/LectureNotes/schedule.md b/doc/LectureNotes/schedule.md index 5bc748484..905af3cef 100644 --- a/doc/LectureNotes/schedule.md +++ b/doc/LectureNotes/schedule.md @@ -5,10 +5,10 @@ This course will be delivered in a hybrid mode, with online lectures and on site 1. Four lectures per week, Fall semester, 10 ECTS. The lectures are in person but will be recorded and linked to this site and the official University of Oslo website for the course; 2. Two hours of laboratory sessions for work on computational projects and exercises for each group. There will also be fully digital laboratory sessions for those who cannot attend; -3. Three projects which are graded and count 1/3 each of the final grade. The deadlines for the projects are October 11 for project 1, November 15 for project 2 and December 13 for project 3. +3. Three projects which are graded and count 1/3 each of the final grade. The deadlines for the projects are October 7 for project 1, November 11 for project 2 and December 9 for project 3. 4. A selected number of weekly assignments; 5. The course is part of the CS Master of Science program, but is open to other bachelor and Master of Science students at the University of Oslo; -6. The course is offered as a FYS-MAT4155 (Master of Science level) and a FYS-MAT3155 (senior undergraduate) course; +6. The course is offered as a FYS-STK4155 (Master of Science level) and a FYS-STK3155 (senior undergraduate) course; 7. Videos of teaching material are available via the links at https://compphysics.github.io/MachineLearning/doc/web/course.html; 8. Weekly emails with summary of activities will be mailed to all participants; @@ -22,12 +22,12 @@ For the reading assignments we use the following abbreviations: - HTF: Hastie, Tibshirani, and Friedman, The Elements of Statistical Learning - AG: Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow -### Week 34 August 23-27 +### Week 34 August 22-26 - Lab Wednesday: Introduction to software and repetition of Python Programming - Lecture Thursday: Introduction to the course, what is Machine Learning and introduction to Linear Regression. -- Video of Lecture August 26, 2021 at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust26.mp4?vrtx=view-as-webpage +- Video of Lecture August 25, 2022 at - Lecture Friday: Basics of Linear Regression -- Video of Lecture August 27, 2021 at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureThursdayAugust27.mp4?vrtx=view-as-webpage +- Video of Lecture August 26, 2022 at - Reading recommendations: - Refresh linear algebra, GBC chapters 1 and 2. @@ -35,12 +35,12 @@ For the reading assignments we use the following abbreviations: - HTF chapters 2 and 3. - See lecture notes for week 34 at https://compphysics.github.io/MachineLearning/doc/web/course.html -### Week 35 August 30-September 3 +### Week 35 August 29-September 2 - Lab Wednesday: Work on exercises 1-3 for week 35 - Thursday: Review of ordinary Least Squares with applications and discussion of Ridge Regression and Singular Value Decomposition -- Video of lecture Thursday at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember2.mp4?vrtx=view-as-webpage. +- Video of lecture Thursday at - Friday: Analysis of Ridge and Lasso Regression and links with Singular Value Decomposition -- Video of lecture Friday at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember3.mp4?vrtx=view-as-webpage +- Video of lecture Friday at - Reading recommendations: - See lecture notes for week 35 at https://compphysics.github.io/MachineLearning/doc/web/course.html. @@ -48,26 +48,25 @@ For the reading assignments we use the following abbreviations: - CMB sections 1.1 and 3.1 -### Week 36 September 6-10 +### Week 36 September 5-9 - Lab Wednesday: Exercises 1 and 2 from week 36 - Lecture Thursday: Summary from last week on SVD, Statistics, probability theory and linear regression -- Video of Lecture https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember9.mp4?vrtx=view-as-webpage +- Video of Lecture - Friday: Linear Regression and links with Statistics, Resampling methods and presentation of first project. -- Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureSeptember10.mp4?vrtx=view-as-webpage +- Video of Lecture - Reading recommendations: - Lectures on Regression for week 36 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Bishop 1.1, 1.2, 2.1, 2.2, 2.3 and 3.1 - Hastie et al chapter 3 -### Week 37 September 13-17 +### Week 37 September 12-16 - Lab Wednesday: Work on Project 1 - Lecture Thursday: Resampling methods, cross-validation and Bootstrap - - Thursday September 16: Summary of Ridge and Lasso with examples and start resampling techniques - - Video of Lecture, first part at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember16Firstpart.mp4?vrtx=view-as-webpage" - - Video of Lecture, second part at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember16SecondPart.mp4?vrtx=view-as-webpage + - Thursday September: Summary of Ridge and Lasso with examples and start resampling techniques + - Video of Lecture - Lecture Friday: More on Resampling methods and summary of linear regression - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember17.mp4?vrtx=view-as-webpage + - Video of Lecture - Reading recommendations: - Lectures on Resampling methods for week 37 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Bishop 1.3 (cross-validation) and 3.2 (bias-variance tradeoff) @@ -75,42 +74,42 @@ For the reading assignments we use the following abbreviations: - Goodfellow et al discuss some of these topics in sections 5.2-5.5. -### Week 38 September 20-24 +### Week 38 September 19-23 - Lab Wednesday: Work on Project 1 - Lecture Thursday: Classification problems and Logistic Regression, from binary cases to several categories - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureSeptember23.mp4?vrtx=view-as-webpage + - Video of Lecture at - Lecture Friday: Logistic Regression and gradient optimization - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember24.mp4?vrtx=view-as-webpage + - Video of Lecture at - Reading recommendations: - See lecture notes for week 38 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Bishop 4.1, 4.2 and 4.3. Not all the material is relevant or will be covered. Section 4.3 is the most relevant, but 4.1 and 4.2 give interesting background readings for logistic regression - Hastie et al 4.1, 4.2 and 4.3 on logistic regression - For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well. -### Week 39 September 27- October 1 +### Week 39 September 26-30 - Lab Wednesday: Work on Project 1 - Lecture Thursday: Gradient Optimization methods - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureSeptember30.mp4?vrtx=view-as-webpage + - Video of Lecture at - Lecture Friday: Gradient methods - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober1.mp4?vrtx=view-as-webpage + - Video of Lecture at - Reading recommendations: - See lecture notes for week 39 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well. -### Week 40 October 4-8 +### Week 40 October 3-7 - Lab Wednesday: Wrap up project 1 - Lecture Thursday: Stochastic gradient descent, automatic differentiation and start discussion of feed-forward Neural Network code for regression and classification - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober7.mp4?vrtx=view-as-webpage + - Video of Lecture at - Lecture Friday: Deep Learning and Neural Networks: the back propagation algorithm - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober8.mp4?vrtx=view-as-webpage + - Video of Lecture at - Reading recommendations: - See lecture notes for week 40 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4 - For stochastic gradient descent we recommend Goodfellow et al chapter 8 -### Week 41 October 11-15 +### Week 41 October 10-14 - Lab Wednesday: Work on project 2 - Lecture Thursday: Deep learning and Neural Networks, developing a code for Neural Networks - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober14.mp4?vrtx=view-as-webpage @@ -121,61 +120,61 @@ For the reading assignments we use the following abbreviations: - For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. chapter 11 and 12 on practicalities and applications -### Week 42 October 18-22 +### Week 42 October 17-21 - Lab Wednesday: Work on project 2 - Lecture Thursday: Solving differential equations with neural networks and start Convolutional Neural Networks and classification problems - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober21.mp4?vrtx=view-as-webpage + - Video of Lecture at - Lecture Friday: Convolutional Neural Networks and classification problems - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureOctober22.mp4?vrtx=view-as-webpage + - Video of Lecture at - Reading recommendations: - See lecture notes for week 42 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - For neural networks we recommend Goodfellow et al chapters 6 and 7. For CNNs, see Goodfellow et al chapter 9. See also chapter 11 and 12 on practicalities and applications -### Week 43 October 25-29 +### Week 43 October 24-28 - Lab Wednesday: Work on project 2 - Lecture Thursday: Recurrent Neural Networks - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober28.mp4?vrtx=view-as-webpage + - Video of Lecture at - Lecture Friday: Recurrent Neural Networks and time series and principal component analysis (PCA) - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober29.mp4?vrtx=view-as-webpage + - Video of Lecture at - Reading recommendations: - See lecture notes for week 43 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - For RNNs, see Goodfellow et al chapter 10 and discussions in chapter 11 and 12 on practicalities and applications - For PCA, see lecture notes chapter 11 and Geron's text chapter 8 -### Week 44 November 1-5 +### Week 44 October 31-November 4 - Lab Wednesday: Work on project 2 - Lecture Thursday: Summary on PCA and discussion of Clustering for unsupervised learning. Decision trees, classification and regression - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureNovember4.mp4?vrtx=view-as-webpage + - Video of Lecture at - Lecture Friday: Decision trees, basic algorithms - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureNovember5.mp4?vrtx=view-as-webpage + - Video of Lecture at - Reading recommendations: - See lecture notes for week 44 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Hastie et al sections 9.1 and 9.2. Geron's text chapter 6 (Decision trees) and chapter 8 on PCA and Clustering -### Week 45 November 8-12 -- Lab Wednesday: Work on project 2, project 3 available. Deadline project 2 is November 15. +### Week 45 November 7-11 +- Lab Wednesday: Work on project 2, project 3 available. - Lecture Thursday: Ensemble methods, bagging and random forests - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureNovember11.mp4?vrtx=view-as-webpage + - Video of Lecture at - Lecture Friday: Boosting and gradient boosting - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureNovember12.mp4?vrtx=view-as-webpage + - Video of Lecture at - Reading recommendations: - See lecture notes for week 45 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Hastie et al chapter 10 -### Week 46 November 15-19 +### Week 46 November 14-18 - Lab Wednesday: Work on project 3 - Lecture Thursday: Support Vector machines - Lecture Friday: Workshop on project 3 - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureNovember19.mp4?vrtx=view-as-webpage + - Video of Lecture at - Reading recommendations: - See lecture notes for week 46 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Hastie et al chapter 12 -### Week 47 November 22-26 +### Week 47 November 21-25 - Lab Wednesday: Work on project 3 - Lecture Thursday: Support Vector Machines - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK4155/h21/forelesningsvideoer/LectureNovember25.mp4?vrtx=view-as-webpage + - Video of Lecture - Lecture Friday: Support Vector Machines and Summary of course - - Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureNovember26.mp4?vrtx=view-as-webpage + - Video of Lecture - Reading recommendations: - See lecture notes for week 47 at https://compphysics.github.io/MachineLearning/doc/web/course.html. - Geron's chapter 5. diff --git a/doc/LectureNotes/teachers.md b/doc/LectureNotes/teachers.md index a1bb4f199..1a65c3772 100644 --- a/doc/LectureNotes/teachers.md +++ b/doc/LectureNotes/teachers.md @@ -9,13 +9,13 @@ * _Office hours_: *Anytime*! Feel free to send an email for planning. Both in person meetings or digital meetings are possible. ## Teaching Assistants Fall semester 2021 -* Øyvind Sigmundson Schøyen, oyvinssc@student.matnat.uio.no -* Stian Bilek, stian.bilek@fys.uio.no -* Linus Ekstrøm, linueks@gmail.com, linus.ekstrom@fys.uio.no -* Nicholas Karlsen, nicholaskarlsen1102@gmail.com, nicholas.karlsen@fys.uio.no -* Bendik Steinsvåg Dalen, b.s.dalen@fys.uio.no -* Philip Karim Sørli Niane, p.k.s.niane@fys.uio.no - +* Bennosh Ashrafi, behnoosh.ashrafi@fys.uio.no +* Frida Marie Engøy Westbye, f.m.e.westby@fys.uio.no +* Ida Torkjellsdatter Storehaug, i.t.storehaug@fys.uio.no +* Joao Guilherme Carvalho Inacio, joaogca@fys.uio.no +* Sigurd Sørlie Rustad, s.s.rustad@fys.uio.no +* Stian Dysthe Bilek stian.bilek@fys.uio.no +* Øyvind Sigmundson Schøyen, oyvinssc@student.matnat.uio.no ## Grading