Learning from Big Data

Course dates – MT – week beginning Monday 26th November 2018 – for Year 1 students
Andrew Zisserman and Andrea Vedaldi

Contents
  •  Discriminative learning
  • Energy based models and max-margin learning.
  • Advanced SVMs and kernel methods
  • Basic stochastic optimization
  • Random forests
  • Neural networks, backprop, max-margin revisited for transfer learning
  • Advanced stochastic optimization
  • Convnets and their application to language, vision and speech
  • Structured output CRFs and SVMs.
Prerequisites
  • MATLAB
  • Basic linear algebra
Other Sources Exercises
  • Practical on large scale classification
  • Practical on Convnets and their applications