Some Course Slides

Deep Learning

  1. Introduction
  2. Ensembles, Boosting and Bagging
  3. Data, Loss, Cost and Optimization
  4. Neural Networks
  5. Convolutional Neural Networks
  6. Regularisation
  7. Optimisation
  8. Sequential Neural Networks
  9. Multivariate Forecasting
  10. Empirical Risk Minimisation
  11. Similarity Learning
  12. Unsupervised Learning
  13. Generative Learning and Density Estimation