Watch Reinforcement Learning: Crash Course AI #9 Video Tutorial


Tutorial Details & Info

Tutorial Title: Reinforcement Learning: Crash Course AI #9
Instructor / Channel: CrashCourse
Lesson Runtime: 11:28 Minutes
Publish Date: October 12, 2019
Total Students / Views: 261,793 views

Follow step-by-step with Reinforcement Learning: Crash Course AI #9 instructor CrashCourse. The total lesson runtime is 11:28 minutes providing step-by-step visual instructions. Follow along to build your skills on any desktop PC, Mac, tablet, or smartphone.

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Course Description & Lesson Notes

Official Video Description:

Reinforcement learning is particularly useful in situations where we want to train AIs to have certain skills we don’t fully understand ourselves. Unlike some of the techniques we’ve discussed so far, reinforcement learning generally only looks at how an AI performs a task AFTER it has completed it. And when an AI completes that task figuring out when and how to reward an AI, called credit assignment, is one of the hardest parts of reinforcement learning. So today, we’re going to explore these ideas, introduce a ton of new terms like value, policy, agent, environment, actions, and states and we’ll show you how we can use strategies like exploration and exploitation to train John Green Bot to find things more efficiently next time. Crash Course AI is produced in association with PBS Digital Studios: https://www.youtube.com/user/pbsdigitalstudios/videos Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse Thanks to the following patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Eric Prestemon, Sam Buck, Mark Brouwer, Indika Siriwardena, Avi Yashchin, Timothy J Kwist, Brian Thomas Gossett, Haixiang N/A Liu, Jonathan Zbikowski, Siobhan Sabino, Zach Van Stanley, Jennifer Killen, Nathan Catchings, Brandon Westmoreland, dorsey, Kenneth F Penttinen, Trevin Beattie, Erika & Alexa Saur, Justin Zingsheim, Jessica Wode, Tom Trval, Jason Saslow, Nathan Taylor, Khaled El Shalakany, SR Foxley, Sam Ferguson, Yasenia Cruz, Eric Koslow, Caleb Weeks, Tim Curwick, David Noe, Shawn Arnold, William McGraw, Andrei Krishkevich, Rachel Bright, Jirat, Ian Dundore -- Want to find Crash Course elsewhere on the internet? Facebook - http://www.facebook.com/YouTubeCrashCourse Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids #CrashCourse #ArtificialIntelligence #MachineLearning

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🎓 Lesson Overview & Learning Outcomes:

Welcome to the step-by-step video guide for Reinforcement Learning: Crash Course AI #9 taught by CrashCourse. This tutorial provides a comprehensive walkthrough designed to take you from foundational principles to practical implementation.

💡 Key Topics Covered in This Course:

  • Core Fundamentals & Setup: Understanding the workspace, essential tools, and initial setup for Reinforcement Learning: Crash Course AI #9.
  • Step-by-Step Practical Demonstration: Hands-on implementation guided by CrashCourse with real-world examples.
  • Best Practices & Key Shortcuts: Time-saving workflows, keyboard shortcuts, and industry-standard recommendations.
  • Troubleshooting & Common Pitfalls: How to avoid common beginner errors and optimize your workflow for peak efficiency.

📋 Recommended Prerequisites & Study Notes:

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