For students and others interested in expanding their knowledge of AI during this period, we thought it might be helpful to ask our researchers what they consider to be the most impactful and insightful resources available to use #AtHomeWithAI (1/9)
Want to know more about reinforcement learning? She recommends @EmmaBrunskill’s’ online lecture series from @StanfordEng. Watch them here: bit.ly/3eAArB9 #AtHomeWithAI
For a more practical and hands-on introduction to Deep Reinforcement Learning, Feryal points to “Spinning up in Deep RL” from @OpenAI. Try it here: bit.ly/2KfQbvw #AtHomeWithAI
For those looking for lectures, slides and Colabs on various #DeepLearning techniques, @feryalmp highlights @Khipu_AI as a favourite. She suggests working through the collection of practical notebooks here: bit.ly/2KkDX4U #AtHomeWithAI
Looking for something that gives an insightful background on neural networks, backpropagation, autoencoders, & more? She recommends the @CompSciOxford ML course - taught by DeepMind research scientist, @NandoDF! Work through it here: bit.ly/3fj6YvU #AtHomeWithAI
Keen to understand multi-task and meta-learning methods? Feryal suggests watching the new lecture series by @chelseabfinn, assistant professor @Stanford and @GoogleAI. Watch them all here: bit.ly/3bowUUl #AtHomeWithAI
Looking to better understand the interplay between neuroscience and AI? @feryalmp suggests ‘Brain Inspired”, a podcast hosted by @pgmid, a favourite for anyone interested in hearing from some of the best minds in that space. Listen here: bit.ly/2ysvGco #AtHomeWithAI
@feryalmp’s final suggestion is for those who want to understand information theory, pattern recognition and neural networks. Watch the late David MacKay’s fantastic in-depth lecture series here: bit.ly/2xJ7NgC
Have your own suggestions for #AtHomeWithAI? Let us know!
Have your own suggestions for #AtHomeWithAI? Let us know!
