Course overview
This course introduces key concepts underlying the development of deep learning techniques. These include: the place of deep learning in the context of statistics and machine learning; the definition, training and validation of deep models. A range of common models and their applications will be presented. The foundational ideas presented in this course will equip students to understand and interpret future developments in this fast moving field.
Course learning outcomes
- Adapt and apply techniques to improve Neural Networks.
- Apply strategies to design and implement a machine learning project using Deep Learning techniques.
- Interpret future developments in Deep Learning based on core concepts presented.
- Analyse Neural Network architectures including Convolutional Neural Networks.
- Critically review and integrate Neural Network solutions to address real-life problems.
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