Machine Learning Courses
This course is taught by Nando de Freitas.
Lecture 13: Hand-writing with recurrent neural networks (Guest speaker: Alex Graves from Google Deepmind)
Lecture 14: Variational autoencoders and image generation (Guest speaker: Karol Gregor from Google Deepmind)
Please click on Timetables on the right hand side of this page for time and location of the practicals. The instructors are Brendan Shillingford and Marcin Moczulsky.
Practicals will use Torch, a powerful programming framework for deep learning that is very popular at Google and Facebook research.
Practical on week 2: (1) Learning Lua and the tensor library. pdf
Practical on week 3: (2) Online and batch linear regression. pdf
Practical on week 4: (3) Logistic regression and optimization. pdf
Practical on week 5: continued previous practical.
Practical on week 6: (4) Feedforward neural networks, and implementing your own layer. pdf
Practical on week 7: (5) Intro to nngraph for graph-shaped modules. pdf
Practical on week 8: (6) Training a LSTM language model. pdf
See the Github repository list for the practicals’ code and technical instructions.
Please click on Timetables on the right hand side of this page for time and location of the classes. The exercises appear below and are due Thursdays at 1pm on the specified week.
Class on Week 3: Problem set. Due 1pm Thursday of Week 2.
Class on Week 5: Problem set. Due 1pm Thursday of Week 4.
Class on Week 7: Problem set. Due 1pm Thursday of Week 6.
Class on Week 8: Problem set. Due 1pm Thursday of Week 7.