updating files

Author: mhjensen

doc/LectureNotes/schedule.md

@@ -1,24 +1,14 @@
-# Teaching schedule with links to material
+# Course setting
 
 
 This course will be delivered in a hybrid mode, with online lectures and on site or online laboratory sessions. 
 
-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 7 for project 1, November 11 for project 2 and December 9 for project 3.
+1. Two 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. fours hours of laboratory sessions for work on computational projects and exercises for each group. 
+3. Three projects which are graded and count 1/3 each of the final grade. 
 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-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;
 
-
-
-##  Weekly Schedule
-
-For the reading assignments we use the following abbreviations:
-- GBC: Goodfellow, Bengio, and Courville, Deep Learning
-- CMB: Christopher M. Bishop, Pattern Recognition and Machine Learning
-- HTF: Hastie, Tibshirani, and Friedman, The Elements of Statistical Learning
-- AG: Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow
-

doc/LectureNotes/teachers.md

@@ -9,22 +9,22 @@
 * _Office hours_: *Anytime*! Feel free to send an email for planning. Both in person meetings or digital meetings are possible.
 
 ##  Teaching Assistants Fall semester 2023
-* Karl Henrik Fredly, [email protected]
-* Daniel Haas Becattini Lima, [email protected]
-* Adam Jakobsen, [email protected]
-* Fahimeh Najafi, [email protected]
 * Ida Torkjellsdatter Storehaug, [email protected]
 * Mia-Katrin Ose Kvalsund, [email protected]
+* Eivind Støland, [email protected]
+* Karl Henrik Fredly, [email protected]
+* Eir Eline Hørlyk, [email protected]
+* Britt S. Haanen, [email protected]
 
 
 ## Practicalities
 
 1. The sessions on Tuesdays and Wednesdays last four hours for each group (four in total) and will include lectures in a flipped mode (promoting active learning) and work on exercices and projects.  The sessions will begin with lectures and questions and answers about the material to be covered every week.
 2. There are four groups, Tuesdays 815am-12pm and 1215pm-4pm and Wednesdays 815am-12pm and 1215pm-4pm. Please sign up as soon as possible for one of the groups. Max capacity per group is 30-40 participants.
 
-3. On Thursdays we have a regular lecture. These lectures start at 1215pm and end at 2pm. The lectures are recorded.
+3. On Mondays we have a regular lecture. The lecture starts at 215pm and ends at 4pm. All lectures are recorded.
 4. Three projects which are graded and count 1/3 each of the final grade;
-5. A selected number of weekly assignments. The weekly assignments can be handed in and for all assignments you can get an extra score of 20 points to the final grade.
+5. A selected number of weekly assignments. The weekly assignments can be handed in and for all assignments you can get an extra score of 10 points to the final grade.
 6. 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;
 7. The course is offered as a so-called _cloned_ course,  FYS-STK4155 at the Master of Science level and FYS-STK3155 as a senior undergraduate)course;
 8. Videos of teaching material are available via the links at https://compphysics.github.io/MachineLearning/doc/web/course.html;
@@ -48,9 +48,44 @@ The final number of points is based on the average of all projects (including ev
 
 | Activity | Percentage of total score |
 |------|-----|
-| First project, _due October 9_ | 33.3% (1/3) |
-| Second  project, _due November 6_ | 33.3% (1.3) |
-| Third project, _due December 11_ |  33.3% (1/3)  |
+| First project, _due October 6_ | 33.3% (1/3) |
+| Second  project, _due November 3_ | 33.3% (1.3) |
+| Third project, _due December 8_ |  33.3% (1/3)  |
 | Extra Credit (not mandatory),  weekly exercise assignments, 10 in total (due each Friday)| 10% |
 
-The first weekly exercise set is scheduled for week 35.
+
+
+## Practicalities
+
+1. The sessions on Tuesdays and Wednesdays last four hours for each group (four in total) and will include lectures in a flipped mode (promoting active learning) and work on exercices and projects.  The sessions will begin with lectures and questions and answers about the material to be covered every week.
+2. There are four groups, Tuesdays 815am-12pm and 1215pm-4pm and Wednesdays 815am-12pm and 1215pm-4pm. Please sign up as soon as possible for one of the groups. Max capacity per group is 30-40 participants.
+
+3. On Mondays  we have a regular lecture. These lectures start at 215pm and ends at 4pm. These lectures are recorded.
+4. Three projects which are graded and count 1/3 each of the final grade;
+5. A selected number of weekly assignments. The weekly assignments can be handed in and for all assignments you can get an extra score of 20 points to the final grade.
+6. The course is offered as a so-called _cloned_ course,  FYS-STK4155 at the Master of Science level and FYS-STK3155 as a senior undergraduate)course;
+7. Weekly email with summary of activities will be mailed to all participants;
+
+
+## Grading
+Grading scale: Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. There are three projects which are graded and each project counts 1/3 of the final grade. The total score is thus the average from all three projects.
+
+The final number of points is based on the average of all projects (including eventual additional points) and the grade follows the following table:
+
+ * 92-100 points: A
+ * 77-91 points: B
+ * 58-76 points: C
+ * 46-57 points: D
+ * 40-45 points: E
+ * 0-39 points: F-failed
+
+## Tentative deadllines for projects
+
+* First project, due October 6, counts 1/3 of final grade
+* Second  project, due November 3, counts 1/3 of final grade
+* Third project, due December 8, counts 1/3 of final grade
+* Extra Credit (not mandatory),  weekly exercise assignments, 10 in total (due Fridays), adds one point per exercises set.
+
+
+
+