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.
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
- 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
- Goodfellow, Bengio and Courville's Deep Learning Book
- Introduction to Machine Learning, Professor Zoubin Ghahramani
- The Neural Network Zoo, Fjodor van Veen
- Tensorflow Tutorials
- Theano Tutorials
- Keras, Deep Learning library for Python
- A Statistical View of Deep Learning, Shakir Mohamed
- Neural Networks, Hugo Larochelle
- Deep Learning Roadmap, Flood Sung