How to Win Slot Machines - Intro to Deep Learning #13

We'll learn how to solve the multi-armed bandit problem (maximizing success for a given slot machine) using a reinforcement learning technique called policy gradients. Code for this video: https://github.com/llSourcell/how_to_win_slot_machines Mike's winning code: https://github.com/xkortex/Siraj_Chatbot_Challenge Vishal's runner up code: https://github.com/erilyth/DeepLearning-Challenges/tree/master/Text_Based_Chatbot this coding challenge was really close, so i'm also going to put code for 3rd place just this time (Eibriel): https://github.com/Eibriel/ice-cream-truck Please Subscribe! And like. And comment. That's what keeps me going. More Learning resources: http://karpathy.github.io/2016/05/31/rl/ http://minpy.readthedocs.io/en/latest/tutorial/rl_policy_gradient_tutorial/rl_policy_gradient.html http://pemami4911.github.io/blog/2016/08/21/ddpg-rl.html http://kvfrans.com/simple-algoritms-for-solving-cartpole/ https://medium.com/@awjuliani/super-simple-reinforcement-learning-tutorial-part-1-fd544fab149 https://dataorigami.net/blogs/napkin-folding/79031811-multi-armed-bandits Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/