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Department of Computer Science and Technology
Computer Laboratory
Teaching
Courses 2018–19
Probabilistic Machine Learning
Course materials
Advanced topics in mobile and sensor systems and data modelling
Algebraic Path Problems
Category Theory
Chip Multiprocessors
Computer Security: Principles and Foundations
Interactive Formal Verification
Introduction to Natural Language Syntax and Parsing
Introduction to networking and systems measurements
Large-scale data processing and optimisation
Machine Learning
Machine Learning for Language Processing
Metaprogramming
Multicore Semantics and Programming
Network Architectures
Overview of Natural Language Processing
Probabilistic Machine Learning
Research Skills Programme
Special topic MT
Advanced Graphics and Image Processing
Advanced Operating Systems
Advanced Topics in Computer Systems
Advanced topics in machine learning and natural language processing
Computer Vision
Cybercrime
Digital Signal Processing
Digital Signal Processing with Computer Music
High performance networking
Interaction with machine learning
Machine learning for programming
Mobile Robot Systems
Special topic LT
Technology and law
Topics in Concurrency
Critical Coding for Digital Humanities
Course pages 2018–19
Probabilistic Machine Learning
Syllabus
Course materials
Information for assessors
Lecture notes etc. are on the webpage for
Engineering Course 4f13
Assessment details etc. are on
Moodle
Coursework notebooks are on
Azure Notebooks
© 2018 Department of Computer Science and Technology, University of Cambridge
Information provided by Prof Carl Rasmussen
