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Pattern Recognition, Neural Networks and Deep Learning

Key information

  • Module code:

    7CCSMPNN

  • Level:

    7

  • Semester:

      Spring

  • Credit value:

    15

Module description

Aims and Learning Outcomes

To introduce a range of methods for solving pattern recognition problems, with a particular emphasis on solving classification problems using supervised learning and neural network approaches.

On successful completion of this module, students will:

  • Be able to understand, analyse and assess material of direct relevance to the subject matter as described in advanced textbooks
  • Be aware of common pattern recognition algorithms and methods, be able to describe their main features, and appropriate applications
  • Be able to apply these methods competently to well-defined problems in standard contexts
  • Have developed problem-solving skills to deal with applications which require pattern recognition techniques

Syllabus

  • Discriminant Functions,
  • Biological and Artificial Neural Networks
  • Multilayer Neural Networks
  • Backpropagation
  • Deep Learning
  • Feature Selection and Extraction
  • Support Vector Machines
  • Ensemble Methods
  • Unsupervised Learning and Clustering

Assessment details

70% examination

30% coursework

Department

Module description disclaimer

King’s College London reviews the modules offered on a regular basis to provide up-to-date, innovative and relevant programmes of study. Therefore, modules offered may change. We suggest you keep an eye on the course finder on our website for updates.

Please note that modules with a practical component will be capped due to educational requirements, which may mean that we cannot guarantee a place to all students who elect to study this module.

Please note that the module descriptions above are related to the current academic year and are subject to change.