Additional resources

Here we list some events, podcasts, blogs, etc that might be of interest.

Podcasts:

  • TalkRL: The Reinforcement Learning Podcast. Very nice interviews with experts and practitioners of reinforcement learning.
  • Talking Machines: Human Conversations about Machine Learning. Lead by experts in the field, very interesting discussions on the ever changing world of ML.
  • Data Skeptic: 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 here.

Virtual meetings and seminars:

Other online resources:

  • stateoftheart.aiNewest 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.
  • Spinning Up in Deep RL: Educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL).
  • Vectorization in Pythona very nice resource for scientific computing using Numpy in Python.
  • Depth First Learning: Compendium of curricula to help understand Machine Learning.

This is of course a very narrow list of all available options on the web.