AWS DeepRacer: Building a Reinforcement Learning Model
With Michael Smith
Liked by 51 users
Duration: 40m
Skill level: Intermediate
Released: 9/16/2022
Course details
Have you ever wanted to find out more about machine learning, but you didn’t know where to begin? AWS DeepRacer is a perfect way to get a fun and useful introduction to machine learning tools, even if you don’t have a technical background. In this course, instructor Michael Smith walks you through the basics of how to use reinforcement learning with AWS DeepRacer—an autonomous one-eighteenth-scale race car designed to test machine learning models by racing on a physical track.
Learn the most important tools for creating your own reinforcement learning algorithm, using built-in DeepRacer resources as your guide. From starting the engine to calibrating the race car and taking the lead on the final lap of the race, Michael helps you understand what reinforcement learning actually does so you can harness it for success in the real world.
Learn the most important tools for creating your own reinforcement learning algorithm, using built-in DeepRacer resources as your guide. From starting the engine to calibrating the race car and taking the lead on the final lap of the race, Michael helps you understand what reinforcement learning actually does so you can harness it for success in the real world.
Skills you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
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Showcase on your LinkedIn profile under “Licenses and Certificate” section
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Download or print out as PDF to share with others
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Share as image online to demonstrate your skill
Meet the instructor
Learner reviews
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Jorge Cordeiro Beleza da Silva
Jorge Cordeiro Beleza da Silva
Computing Studies & Information Systems | Douglas College | Cybersecurity | New Westminster, BC
Contents
What’s included
- Practice while you learn 1 exercise file
- Test your knowledge 4 quizzes
- Learn on the go Access on tablet and phone
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