View Proposal

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Proposer

Hani Ragab

Title

Machine Learning API

Goal

Design and build a machine learning API for sparse matrices

Description

Sparse matrices are matrices whose elements are mostly zeroes. Not taking that fact into account results in sub-optimal manipulation of the matrix and a waste of CPU time, RAM and storage. Our objective is to: - Build a library that implements one or more feature selection algorithms, such as Chi-2, mutual information, and information gain - Implement one or more machine learning algorithms - (Optionally) parallelise computations. - (Optionally) integrate our library in R. Programming Language: - C, C++ - (Optionally) Assembly - Certainly not Java :) Some Wikipedia Reading: - Sparse matrices: https://en.wikipedia.org/wiki/Sparse_matrix - Feature selection: https://en.wikipedia.org/wiki/Feature_selection - Machine learning: https://en.wikipedia.org/wiki/Machine_learning The project can be taken a group of students where each of them will be working on a particular component of the API.

Resources

Background

C/C++

Url

Difficulty Level

Variable

Ethical Approval

None

Number Of Students

5

Supervisor

Hani Ragab

Keywords

Degrees

Bachelor of Science in Computer Science
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Data Science
Master of Science in Software Engineering