Machine Learning (CS331)

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Oct 14, 2013 (3 years and 7 months ago)

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Outline
Credit Points
Machine Learning (CS331)
T.Vetter,
T.Albrecht,R.Knothe,M.Luthi
March 1,2010
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
Machine Learning (CS331)
Docent Prof.Dr.Thomas Vetter
Assistants Dr.Reinhard Knothe,Thomas Albrecht,Marcel Luthi
Schedule Lectures:Monday 14-16
Thursday 10-12
Exercise:Monday 16-18
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
The course is divided into two parts.
Part I
theoretical foundations of machine learning.
precise,mathematical setting of the learning problem
Part II
focus on a practical application of machine learning.
Automatic face recognition
prior-knowledge about human faces:Models are learned from
a dataset of example faces.
Registration
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
The course is divided into two parts.
Part I
theoretical foundations of machine learning.
precise,mathematical setting of the learning problem
Part II
focus on a practical application of machine learning.
Automatic face recognition
prior-knowledge about human faces:Models are learned from
a dataset of example faces.
Registration
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
The course is divided into two parts.
Part I
theoretical foundations of machine learning.
precise,mathematical setting of the learning problem
Part II
focus on a practical application of machine learning.
Automatic face recognition
prior-knowledge about human faces:Models are learned from
a dataset of example faces.
Registration
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
The course is divided into two parts.
Part I
theoretical foundations of machine learning.
precise,mathematical setting of the learning problem
Part II
focus on a practical application of machine learning.
Automatic face recognition
prior-knowledge about human faces:Models are learned from
a dataset of example faces.
Registration
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
The course is divided into two parts.
Part I
theoretical foundations of machine learning.
precise,mathematical setting of the learning problem
Part II
focus on a practical application of machine learning.
Automatic face recognition
prior-knowledge about human faces:Models are learned from
a dataset of example faces.
Registration
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
The course is divided into two parts.
Part I
theoretical foundations of machine learning.
precise,mathematical setting of the learning problem
Part II
focus on a practical application of machine learning.
Automatic face recognition
prior-knowledge about human faces:Models are learned from
a dataset of example faces.
Registration
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
Part I:Theory
Lectures:Mo/Do
Excercise:Mo
Correction/Discussion
homework
Script/Slides
Part II:practical application
the student have to read
5 scientic papers.
Lectures/Discussion
about the papers:
Mo/Do
Excercise:Mo
Correction/Discussion
homework
Slides/Papers
We expect that the students rework the lecture,read the papers
and do the homework.
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
Part I:Theory
Lectures:Mo/Do
Excercise:Mo
Correction/Discussion
homework
Script/Slides
Part II:practical application
the student have to read
5 scientic papers.
Lectures/Discussion
about the papers:
Mo/Do
Excercise:Mo
Correction/Discussion
homework
Slides/Papers
We expect that the students rework the lecture,read the papers
and do the homework.
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
Part I:Theory
Lectures:Mo/Do
Excercise:Mo
Correction/Discussion
homework
Script/Slides
Part II:practical application
the student have to read
5 scientic papers.
Lectures/Discussion
about the papers:
Mo/Do
Excercise:Mo
Correction/Discussion
homework
Slides/Papers
We expect that the students rework the lecture,read the papers
and do the homework.
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
Part I:Theory
Lectures:Mo/Do
Excercise:Mo
Correction/Discussion
homework
Script/Slides
Part II:practical application
the student have to read
5 scientic papers.
Lectures/Discussion
about the papers:
Mo/Do
Excercise:Mo
Correction/Discussion
homework
Slides/Papers
We expect that the students rework the lecture,read the papers
and do the homework.
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
Part I:Theory
Lectures:Mo/Do
Excercise:Mo
Correction/Discussion
homework
Script/Slides
Part II:practical application
the student have to read
5 scientic papers.
Lectures/Discussion
about the papers:
Mo/Do
Excercise:Mo
Correction/Discussion
homework
Slides/Papers
We expect that the students rework the lecture,read the papers
and do the homework.
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
Part I:Theory
Lectures:Mo/Do
Excercise:Mo
Correction/Discussion
homework
Script/Slides
Part II:practical application
the student have to read
5 scientic papers.
Lectures/Discussion
about the papers:
Mo/Do
Excercise:Mo
Correction/Discussion
homework
Slides/Papers
We expect that the students rework the lecture,read the papers
and do the homework.
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
Part I:Theory
Lectures:Mo/Do
Excercise:Mo
Correction/Discussion
homework
Script/Slides
Part II:practical application
the student have to read
5 scientic papers.
Lectures/Discussion
about the papers:
Mo/Do
Excercise:Mo
Correction/Discussion
homework
Slides/Papers
We expect that the students rework the lecture,read the papers
and do the homework.
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
Part I:Theory
Lectures:Mo/Do
Excercise:Mo
Correction/Discussion
homework
Script/Slides
Part II:practical application
the student have to read
5 scientic papers.
Lectures/Discussion
about the papers:
Mo/Do
Excercise:Mo
Correction/Discussion
homework
Slides/Papers
We expect that the students rework the lecture,read the papers
and do the homework.
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
How to get the Credit Points?
50% of the homework
oral exam
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
How to get the Credit Points?
50% of the homework
oral exam
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)
Outline
Credit Points
How to get the Credit Points?
50% of the homework
oral exam
T.Vetter,T.Albrecht,R.Knothe,M.Luthi
Machine Learning (CS331)