Update beamerweek34.do.txt

This commit is contained in:
Morten Hjorth-Jensen
2023-08-14 10:28:41 +02:00
parent 75a24defea
commit 9e3610b0f8
+3 -4
View File
@@ -67,7 +67,7 @@ Reading recommendations this week: Refresh linear algebra, GBC chapters 1 and 2.
===== Communication channels =====
* Chat and communications via URL:"canvas.uio.no"
* _Slack_ channel: machinelearninguio.slack.com
* _Slack_ channel: machinelearninguio.slack.com, see invitation sent by email
!split
@@ -76,9 +76,8 @@ Reading recommendations this week: Refresh linear algebra, GBC chapters 1 and 2.
!bblock
* Three compulsory projects. Electronic reports only using "Canvas":"https://www.uio.no/english/services/it/education/canvas/" to hand in projects and "git":"https://git-scm.com/" as version control software and "GitHub":"https://github.com/" for repository (or "GitLab":"https://about.gitlab.com/") of all your material.
* Evaluation and grading: The three projects are graded and each counts 1/3 of the final mark. No final written or oral exam.
o For the last project each group/participant submits a proposal or works with suggested (by us) proposals for the project.
o If possible, we would like to organize the last project as a workshop where each group makes a poster and presents this to all other participants of the course
o Poster session where all participants can study and discuss the other proposals.
o For the last project each group/participant submits a proposal or works with suggested (by us) proposals for the project. The hope is that the last project can be aligned with your interests/research project(s).
o If possible, we would like to organize the last project as a workshop where each group presents this to all other participants of the course
o Based on feedback etc, each group finalizes the report and submits for grading.
* Python is the default programming language, but feel free to use C/C++ and/or Fortran or other programming languages. All source codes discussed during the lectures can be found at the webpage and "github address":"https://github.com/CompPhysics/MachineLearning/tree/master/doc/Programs" of the course.
!eblock