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Study-Unit Description

Study-Unit Description


CODE MAT3771

 
TITLE Numerical Methods for Machine Learning

 
UM LEVEL 03 - Years 2, 3, 4 in Modular Undergraduate Course

 
MQF LEVEL 6

 
ECTS CREDITS 4

 
DEPARTMENT Mathematics

 
DESCRIPTION - Solution of equations by iteration;
- Solution of systems of linear equations;
- One dimensional search methods;
- Unconstrained optimization with the method of steepest descent;
- Polynomial Interpolation;
- Numerical Integration – Newton – Cotes Formulae;
- Polynomial Approximation in Different Norms;
- Numerical Integration – Gauss Quadrature;
- Piecewise Polynomial Approximation (optional).

Study-Unit Aims:

The purpose of this study-unit is to provide a theoretical introduction to essential topics of numerical analysis such as curve fitting, interpolation and numerical integration.

Learning Outcomes:

1. Knowledge & Understanding:

By the end of the study-unit the student will be able to:

- Explain the concepts of iteration and approximation and compare the different approximation techniques;
- Solve algebraic systems by iterative techniques;
- Compare the approximations in different norms with analysing their error quantities;
- Explain the necessity of the numerical integration and perform suitable techniques for numerical calculation of integration.

2. Skills:

By the end of the study-unit the student will be able to:

- Solve algebraic systems by iterative techniques;
- Calculate integrals by numerical methods;
- Find best approximation for given set of data.

Main Text/s and any supplementary readings:

Main Texts:

- E. Süli and D. Mayers. An introduction to Numerical Analysis. Cambridge University Press, 2003.

Supplementary Readings:

- S. R. Esfandiari. Numerical Methods for Engineers and Scientists Using Matlab, Crc Press, Second Edition, 2013.
- V. L. Fausett. Applied Numerical Analysis Using Matlab. Pearson Prentice Hall, 2008.

 
ADDITIONAL NOTES Leads to: MAT3772

 
STUDY-UNIT TYPE Lecture, Independent Study and Project

 
METHOD OF ASSESSMENT
Assessment Component/s Assessment Due Sept. Asst Session Weighting
Project SEM2 Yes 20%
Examination (2 Hours) SEM2 Yes 80%

 
LECTURER/S Onur Baysal

 

 
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the description above applies to study-units available during the academic year 2025/6. It may be subject to change in subsequent years.

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