EPISODE · Sep 25, 2018 · 10 MIN
Q Learning for Trading
from Siraj Raval
We can use reinforcement learning to build an automated trading bot in a few lines of Python code! In this video, i'll demonstrate how a popular reinforcement learning technique called "Q learning" allows an agent to approximate prices for stocks in a portfolio. The literature of reinforcement learning is incredibly rich. There are so many concepts, like TD-Learning and Actor-Critic for example, that have real-world potential. I hope this video gives you insight into how this incredibly powerful yet simple algorithm works, enjoy! Code for this video: https://github.com/llSourcell/Q-Learning-for-Trading Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval The School of AI: https://www.theschool.ai Github Syllabus: https://github.com/llSourcell/Move_37_Syllabus More learning resources: http://www.wildml.com/2018/02/introduction-to-learning-to-trade-with-reinforcement-learning/ http://cs229.stanford.edu/proj2009/LvDuZhai.pdf https://medium.com/@gaurav1086/machine-learning-for-algorithmic-trading-f79201c8bac6 https://github.com/edwardhdlu/q-trader http://www1.mate.polimi.it/~forma/Didattica/ProgettiPacs/BrambillaNecchi15-16/PACS_Report_Pierpaolo_Necchi.pdf Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 #QLearningForTrading #SirajRaval
What this episode covers
We can use reinforcement learning to build an automated trading bot in a few lines of Python code! In this video, i'll demonstrate how a popular reinforcement learning technique called "Q learning" allows an agent to approximate prices for stocks in a portfolio. The literature of reinforcement learning is incredibly rich. There are so many concepts, like TD-Learning and Actor-Critic for example, that have real-world potential. I hope this video gives you insight into how this incredibly powerful yet simple algorithm works, enjoy! Code for this video: https://github.com/llSourcell/Q-Learning-for-Trading Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval The School of AI: https://www.theschool.ai Github Syllabus: https://github.com/llSourcell/Move_37_Syllabus More learning resources: http://www.wildml.com/2018/02/introduction-to-learning-to-trade-with-reinforcement-learning/ http://cs229.stanford.edu/proj2009/LvDuZhai.pdf https://medium.com/@gaurav1086/machine-learning-for-algorithmic-trading-f79201c8bac6 https://github.com/edwardhdlu/q-trader http://www1.mate.polimi.it/~forma/Didattica/ProgettiPacs/BrambillaNecchi15-16/PACS_Report_Pierpaolo_Necchi.pdf Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 #QLearningForTrading #SirajRaval
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Q Learning for Trading
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