Deep Learning Reading Group
This group is no longer running; however, I am keeping this page for reference only. If you wish to be involved in machine/deep learning in Warwick, please check out the newly formed Machine Learning Research Group
This is a complementary group to the Machine Learning Reading Group. We meet informally every fortnight to discuss topics from the Deep Learning Book by Goodfellow, Bengio and Courville. This book is now available in print. You can order your copy from Amazon.
Please feel free to come along for one or more of our sessions. We offer free biscuits and interesting discussions about Deep Learning.
If you are a regular member of this reading group (or would like to be), can you please drop me (Ayman) an email so I can add you to the mailing list.
Please note that the aim of this group is to collaboratively learn about Deep Learning. Therefore, we will only publish a provisional schedule of the topics subject to change depending on the pace and participants' feedback.
Dates and Topics (Provisional):
- Please check back again in September
Previous Meetings:
- 10/11/2016: Introduction to Machine Learning (Chapters 1-5)
- 24/11/2016: Introduction to ML (continued) + Multi-Layered Perceptron (Chapters 5-6)
- 08/12/2016: Backpropagation and Regularisation (Chapters 6-7)
- 16/01/2017: Dropout and Optimisation (Chapters 7-8)
- 30/01/2017: Batch Normalisation and Convolutional Neural Networks (Chapters 8-9)
- 27/02/2017:Convolutional Neural Networks (continued) (Chapter 9)
- 13/03/2017: Takeover by Jim Skinner!
- 27/03/2017: Recurrent Neural Networks (Chapter 10)
- 10/04/2017: Is Bayesian Deep Learning the most brilliant thing ever! - NIPS Workshop Panel Discussion
- 24/04/2017: RNNs Continued and LSTMs (Chapter 10)
- 08/05/2017: Linear Factor Models (Chapter 13)
- 05/06/2017: Keras Demo
- 03/07/2017: Autoencoders (Chapter 14)
- 17/07/2017: Variational Autoencoders
Resources:
- Goodfellow, Bengio and Courville's Deep Learning BookLink opens in a new window
- Introduction to Machine LearningLink opens in a new window, Professor Zoubin Ghahramani
- deeplearning.netLink opens in a new window
- The Neural Network ZooLink opens in a new window, Fjodor van Veen
- Tensorflow TutorialsLink opens in a new window
- Theano TutorialsLink opens in a new window
- KerasLink opens in a new window, Deep Learning library for Python
- A Statistical View of Deep LearningLink opens in a new window, Shakir Mohamed
- Neural Networks, Hugo Larochelle
- Deep Learning Roadmap, Flood Sung
Time and Location:
16:00-17:00
Room D1.07
Mathematics & Statistics Building
Contact:
Ayman Boustati (organiser)