Machine Learning Syllabus
This page contains Syllabus of Machine Learning of BCA.
Title | Machine Learning |
Short Name | |
Course code | CACS456 |
Nature of course | Theory + Practical |
Eighth Semester | |
Full marks | 60 |
Pass marks | 24 |
Credit Hrs | 6 |
Elective/Compulsary | Elective |
Course Description
Course Description
This course presents comprehensive introduction to several topics on basic concepts and techniques of Machine Learning (ML). It also explores the understanding of the Supervised and unsupervised learning techniques,probability based learning techniques, performance evaluation of ML algorithms and applications of ML.
Course objectives
Upon completion of this course, students should be able to 1. Explain the concept of supervised, unsupervised and semi-supervised learning. 2. Develop algorithms to learn linear and non- linear models using software. 3. Perform creative work in the field machine learning to solve given problem.