ucl deepmind lecture series
Deep learning plays a vital role in this epoch of artificial intelligence.
In this lecture series, leading research scientists from leading AI research lab, DeepMind, will give 12 lectures on an exciting selection of topics in Deep Learning, ranging from the fundamentals of training neural networks via advanced ideas around memory, attention, and generative modelling to the important topic of responsible innovation. The 12 video lectures cover topics from neural network foundations and optimisation through to generative adversarial networks and responsible innovation. In recognition of this huge impact, the 2019 Turing Award, the highest honour in computing, was awarded to pioneers of Deep Learning.In this series, DeepMind Research Scientists and Research Engineers deliver 12 lectures on a range of topics in Deep Learning.DeepMind Research Scientist and UCL professor Thore Graepel explains DeepMind's machine learning based approach towards AI.DeepMind Research Scientist Wojciech Czarnecki covers the basics of how neural networks operate, learn and solve problems.DeepMind Research Scientist Sander Dieleman takes a closer look at convolutional network architectures through several case studies.DeepMind Research Scientist Viorica Patraucean introduces classic computer vision tasks beyond image classification and describes state of the art models for each, together with standard benchmarks.DeepMind Research Scientist James Martens covers the fundamentals of gradient-based optimisation methods, and their application to training neural networks.DeepMind Research Scientist Marta Garnelo focuses on sequential data and how machine learning methods have been adapted to process this particular type of structure.DeepMind Research Scientist Felix Hill discusses the motivation for modelling language with ANNs, and unsupervised and representation learning for language.DeepMind Research Scientist Alex Graves covers a contemporary attention mechanisms, including the implicit attention present in any deep network.DeepMind Research Scientist Jeff Donahue & Research Engineer Mihaela Rosca discuss the theory behind GAN models, optimisation and improvements.DeepMind Research Scientist Irina Higgins and DeepMind Research Engineer Mihaela Rosca give an overview the historical role of unsupervised representation learning.DeepMind Research Scientist Andriy Mnih explores latent variable models, a powerful and flexible framework for generative modelling.DeepMind Research Scientists Chongli Qin and Iason Gabriel explore questions like: what can we do to build algorithms that are safe, reliable and robust? The Deep Learning Lecture Series 2020 is a collaboration between DeepMind and the UCL Centre for Artificial Intelligence. The Deep Learning Lecture Series is a collaboration between DeepMind and the UCL Centre for Artificial Intelligence. The resulting applications are touching all of our lives in areas such as healthcare and medical research, human-computer interaction, communication, transport, conservation, manufacturing and many other fields of human endeavour. In this lecture series, research scientists from leading AI research lab, DeepMind, deliver 12 lectures on an exciting selection of topics in Deep Learning, ranging from the fundamentals of training neural networks via advanced ideas around memory, attention, and generative modelling to the important topic of responsible innovation. We are excited to present the Deep Learning Lecture Series - a collaboration between DeepMind and the UCL Centre for Artificial Intelligence. Knowingly or unknowingly everyday we are utilising the windfalls of deep learning methods.Hence, therefore,DeepMind and the UCL Centre for Artificial Intelligence worked together to … Over the past decade, Deep Learning has evolved as the leading artificial intelligence paradigm providing us with the ability to …
The Deep Learning Lecture Series 2020: DeepMind and the UCL Centre collaboration for Artificial Intelligence. UCL x DeepMind Deep Learning Lecture Series - General.
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