Teaching Responsibility
LJMU Schools involved in Delivery:
Computer Science and Mathematics
Learning Methods
Lecture
Practical
Tutorial
Module Offerings
7143COMP-SEP-CTY
Aims
To develop knowledge and an understanding of machine learning at masters level and provide guidance on the design and development of machine learning projects using both theory and practice.
To provide an understanding of a range of tools, techniques, algorithms, and data processing approaches.
To critically evaluate machine learning methodologies and their appropriate use to solve real-world problems.
Learning Outcomes
1.
Demonstrate advanced understanding of the theoretical principles and objectives of Machine Learning (ML)
2.
Critically evaluate and apply advanced ML concepts and techniques
3.
Select appropriate ML algorithms to solve particular tasks
4.
Critically evaluate ML algorithms to determine their strengths and weaknesses
5.
Implement, validate and test different ML algorithms introduced in the module using Python and associated frameworks
Module Content
Outline Syllabus:1. Machine Learning Fundamentals
2. Data Engineering
3. Unsupervised Learning
4. Supervised Learning
5. Linear Regression
6. Logistic Regression
7. Random Forests and Ensemble Methods
8. Support Vector Machines
9. Dimensionality Reduction
10. Feature Engineering
11. Performance, Validation and Model Interpretation; Large Scale Machine Learning
Module Overview:
This module provides fundamental skills required in machine learning to solve real-world problems. These skills will help to equip the student with the fundamental principles of machine learning to support advanced topics taught in the course. Furthermore, these skills will be practical core requirements for a successful career as a machine learning engineer in industry.
This module provides fundamental skills required in machine learning to solve real-world problems. These skills will help to equip the student with the fundamental principles of machine learning to support advanced topics taught in the course. Furthermore, these skills will be practical core requirements for a successful career as a machine learning engineer in industry.
Additional Information:This module provides fundamental skills required in machine learning to solve real-world problems. These skills will help to equip the student with the fundamental principles of machine learning to support advanced topics taught in the course. Furthermore, these skills will be practical core requirements for a successful career as a machine learning engineer in industry.