This module aims to equip students with essential machine learning and text mining skills. Students will be introduced to the up-to-date analytics models and applications for both structured and unstructured data. This course will focus on the techniques and methods rather than the maths behind these models. This course should be taken after ACC905 Data Analysis with Python.
A Identify the difference between a supervised (classification) and unsupervised (clustering) technique B Identify which technique they need to apply for a particular dataset and need C Write python code for data analytics with machine learning models D Apply basic natural language processing (NLP) tool E Write a program to identify text sentiment F Complete text analytics-related tasks by calling API
This module will be taught using a combination of lectures and lab sessions. Learning will also be reinforced by appropriate readings and practices from the course resources.