Subject: Subject Sylbus: Algebraic Methods for Data Science - 095295

Algebraic Methods for Data Science - 095295
Credit
Points
3.5
 
Given In
Semester
a
 
  Lecture Exercise Laboratory Project or
Seminar
House
Work
Weekly
Hours
3 1      

Determination of the grade according to progress during the semester and a final examination.


Prerequisites: ( Discrete Mathematics (for I.E) 094345
and Calculus 2M 104032
and Algebra a 104166
and Introduction to Computer Science H 234117 )
or ( Discrete Mathematics 094346
and Linear Algebra M 104019
and Calculus 2N 104020
and Introduction to Computer Science 234111 )
or ( Discrete Mathematics 094346
and Algebra 1/Extended 104016
and Calculus 2N 104020
and Introduction to Computer Science N 234221 )
or ( Discrete Mathematics 094346
and Linear Algebra M 104019
and Calculus 2N 104020
and Introduction to Computer Science N 234221 )
 
Overlapping Courses: Numerical Algorithms 234125


Complementary Topics in Linear Algebra (Inner Product Spaces, Norms, Orthonormal Bases, Eigen-Values), Matrix Decomposition (Spectral Decomposition Theorem, Svd), Linear Systems (Gauss Elimination Process), Lest Squares, Iterative Methods (Power Method), Linear Programming (Simplex Method, Duality, Applications to Classification and Sparse Solutions to Linear Systems), Perturbation Theorems for Matrix Decomposition, Introduction to Tensors.




System of hours to the semesters
Semester Previous Semester information 01/2020 2020/2021 Winter Semester


Textbooks
PublishedPublisherAuthorsBook
2013the johns hopkins uni. pressg. golun and c. van loanmatrix computation
2014cambridge uni. pressg. calafiore and l. el ghaouioptimization models

Created in 22/04/2021 Time 15:22:46