Additional resources
Here we list some events, podcasts, blogs, etc that might be of interest.
Podcasts:
- : The Reinforcement Learning Podcast. Very nice interviews with experts and practitioners of reinforcement learning.
- : Human Conversations about Machine Learning. Lead by experts in the field, very interesting discussions on the ever changing world of ML.
- : Weekly interviews with leading researchers and practitioners on data science, machine learning, and artificial intelligence.
- A post that describes 10 top podcasts on AI, Data Science and Machine Learning can be found .
Virtual meetings and seminars:
- : Online seminars with the latest advances in reinforcement learning theory.
- : Two weekly 30-minute talks which include theoretical, computational, and applied aspects of integer and combinatorial optimization.
- : A weekly online seminar on random topics on mathematical foundations of machine learning, statistics and optimization.
- : Virtual Seminar series organized by the Stochastic Programming Society
- : meetings and talks by members of the Montréal Machine Learning and Optimization (MTL MLOpt)
- : Very nice talks by leading figures in theoretical optimization.
Other online resources:
- : Newest developments in the fields of AI and ML in an easily consultable repository for state of the art, quantifiable results across tasks on AI, ML and RL.
- : Educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL).
- : a very nice resource for scientific computing using Numpy in Python.
- : Compendium of curricula to help understand Machine Learning.
This is of course a very narrow list of all available options on the web.