320513 Machine Learning
6cp; onlineRequisite(s): (230708 Foundation Studio AND 240753 Customer Analytics AND 320146 Data Visualisation and Visual Analytics AND (430031 Python Programming for Data Processing OR 420047 Data Processing Using Python))
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.
Anti-requisite(s): 31005 Machine Learning AND 32513 Advanced Data Analytics Algorithms
Recommended studies: knowledge of database technologies
Postgraduate
Description
This subject introduces the essential elements of machine learning - a technique that enables a machine to learn from data and automatically derive or enhance its strategy to perform its tasks. Taking a practical and technical approach, the Machine Learning subject guides learners to the important principles that underlie highly successful machine learning techniques with hands-on experience.
This subject presents learners with core concepts in machine learning as well as a generic framework for machine learning projects. Different learning models, including Decision Trees, Random-Forest, and Neural Networks are discussed and practised with real-world applications dealing with structured (tabular), semi-structured (text) and unstructured data (image).
Detailed subject description.