Course co-ordinator(s): Dr Neamat El Gayar (Dubai), Md Azher Uddin (Dubai), Dr John See (Malaysia).
Aims:
This course aims to provide the students with knowledge and skills in applied text analytics focusing on Machine Learning and Natural Language Processing tools.
In particular the course:
- Presents the area of text analytics and provides fundamental tools to extract, represent and analyse information from text sources using machine learning models
- Provides a fundamental understanding of concepts and tools to build effective language aware systems and applications
- Presents basic understanding of deep learning models for Natural Language Processing applications and related research
- Discusses current research advances, business cases and future direction of the field
Detailed Information
Course Description: Link to Official Course Descriptor.
Pre-requisites: none.
Location: Dubai, Edinburgh, Malaysia.
Semester: 2.
Syllabus:
Following topics will be covered with varying levels of depth:
- Overview on ML models, techniques and use cases & ML project design.
- Language model & text processing principles
- Text classification & visualization
- Text Clustering & topic modelling
- Context-aware text analysis & n-gram model
- Chatbots
- Scaling text analytics
- A deep learning approach to NLP:
o Sequence models (ex: RNN, BRNN, LSTM ) & transfer learning
o Applications in Named Entity Recognition, learning word-embeddings, machine translation, sentiment classification
- Research Directions and Business Cases
SCQF Level: 10.
Credits: 15.