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Department of Computer Science and Technology
Computer Laboratory
Teaching
Courses 2019–20
Machine Learning for Language Processing
Course materials
Advanced Graphics and Image Processing
Advanced Topics in Computer Architecture
Advanced Topics in Mobile Systems and Mobile Data Machine Learning
Algebraic Path Problems
Automated Reasoning
Category Theory
Cybercrime
Data Science: principles and practice
Digital Signal Processing
Hardware Security
Interactive Formal Verification
Introduction to Natural Language Syntax and Parsing
Introduction to networking and systems measurements
Large-scale data processing and optimisation
Machine Learning for Language Processing
Multicore Semantics and Programming
Network Architectures
Overview of Natural Language Processing
Probabilistic Machine Learning
Research Skills Programme
Technology, law and society
Advanced Operating Systems
Advanced Topics in Computer Systems
Advanced topics in machine learning and natural language processing
Affective Computing
Computer Security: Principles and Foundations
Computer Vision
High performance networking
Machine learning for programming
Mobile Robot Systems
Topics in Concurrency
Topics in Logic and Complexity
Course pages 2019–20
Machine Learning for Language Processing
Syllabus
Course materials
Assessment
01. Introduction
02. Classification with the perceptron
03. Probabilistic Classification
04. Optimization fundamentals
05. Feedforward Neural Networks
06. Introduction to Structured Prediction
14. Incremental Structured Prediction
15. Matrix Factorization
16. Unlabeled data
© 2019 Department of Computer Science and Technology, University of Cambridge
Information provided by
Dr Andreas Vlachos