Uploaded September 2021 | Updated September 2026, 1 week ago
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Andrew G. Barto is a former computer scientist and professor emeritus and known for his research on learning in machines and animals. He worked on developing learning algorithms that are useful for engineering applications but that also make contact with learning as studied by psychologists and neuroscientists.
When it comes to reinforcement learning (RL), it has been immensely gratifying for Andrew to participate in establishing new links between RL and methods from the theory of stochastic optimal control. Especially exciting are the connections between temporal difference (TD) algorithms and the brain's dopamine system.
Plenty of people know him as one of the authors of the great book βReinforcement Learning: An Introductionβ which he wrote with his colleague Richard Sutton.
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π My website - jousefmurad.com
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πΈ Instagram - instagram.com/jousefmrd
π¦ Twitter - twitter.com/Jousefm2
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RECOMMENDATIONS
==================
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CONTACT:
-----------------
If you need help or have any questions or want to collaborate feel free to reach out to me via email: engineeringmkl@gmail.com
#MachineLearning
#ArtificialIntelligence
#ReinforcementLearning
Disclaimer: Some of these links are affiliate links which make me earn a small commission when you make a purchase at no additional cost to you.
π APEX Consulting: theapexconsulting.com
π Website: jousefmurad.com
π¬ Full podcast: youtube.com/watch?v=D-VULoe0IPI
Andrew G. Barto is a former computer scientist and professor emeritus and known for his research on learning in machines and animals. He worked on developing learning algorithms that are useful for engineering applications but that also make contact with learning as studied by psychologists and neuroscientists.
When it comes to reinforcement learning (RL), it has been immensely gratifying for Andrew to participate in establishing new links between RL and methods from the theory of stochastic optimal control. Especially exciting are the connections between temporal difference (TD) algorithms and the brain's dopamine system.
Plenty of people know him as one of the authors of the great book βReinforcement Learning: An Introductionβ which he wrote with his colleague Richard Sutton.
ONLINE PRESENCE
================
π My website - jousefmurad.com
π My weekly science newsletter - jousef.substack.com
πΈ Instagram - instagram.com/jousefmrd
π¦ Twitter - twitter.com/Jousefm2
SUPPORT MY WORK
=================
π Science Merch: engineered-mind.creator-spring.com
π Become my Patreon: patreon.com/theengiineer
π§ Subscribe for more free videos: bit.ly/2RLmMxq
RECOMMENDATIONS
==================
π₯ 1 Month Free of Skillshare Premium: bit.ly/3E3bXwC
π Books on AI, Data Science & Programming: bit.ly/2I1lUD1 - use "podengineered20" to get a 40% discount!
CONTACT:
-----------------
If you need help or have any questions or want to collaborate feel free to reach out to me via email: engineeringmkl@gmail.com
#MachineLearning
#ArtificialIntelligence
#ReinforcementLearning
Disclaimer: Some of these links are affiliate links which make me earn a small commission when you make a purchase at no additional cost to you.
![[Teaser] From Academia to Aston Martin F1 - Mohamed Aly Sayed](https://i.ytimg.com/vi/hv2hiq2SQow/mqdefault.jpg "[Teaser] From Academia to Aston Martin F1 - Mohamed Aly Sayed
Full Episode: https://www.youtube.com/watch?v=FdXKvXCrljw&ab_channel=JousefMurad%7CDeepDive
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π Mo on LinkedIn: https://www.linkedin.com/in/mohamedsayedh/
Mohamed Aly Sayed is an aerospace engineer who holds a PhD in particle tracking and turbulent flow modeling. He has worked for Aston Martinβs F1 team and is currently a CFD development engineer for WIN-GD. He is also the founder of Simulitica, a CFD company where he builds efficient CFD GUI tools for companies.
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π¦ Twitter - https://twitter.com/Jousefm2
CONTACT:
ββββββββ
If you need help or have any questions or want to collaborate feel free to reach out to me via email: support@jousefmurad.com
#engineering
#cfd
#formula1
Disclaimer: Some of these links are affiliate links that make me earn a small commission when you make a purchase at no additional cost.
Podcast Recorded: September 6th, 2024 - Subscriber Release Count: 37,008.")
