Deep Dive – AWS DeepRacer League F1 ProAm

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AWS Partner: Bigmate
Published on 18 Sep 2020, 23:14
Get rolling with machine learning at amzn.to/32GirRZ
Can’t get enough F1? Rejoin our AWS DeepRacer experts, Brian Townsend and Eddie Calleja, along with F1’s Rob Smedley as we dive deeper into the machine learning strategies employed by FORMULA 1 drivers Daniel Ricciardo and Tatiana Calderón during the recent DeepRacer League F1 ProAm Grand Prix.

You’ll also meet 2 of the fastest developers in the AWS DeepRacer League—Ray Goh and James Jennens—as they dissect tricks and techniques they’ve learned over countless laps around the track. We’ll uncover key techniques such as log analysis, optimization of racing line, hyperparameter tuning, and performance envelopes to apply to your next DeepRacer build. Next month, it could be you atop the podium!

0:00 Meet the Experts
1:14 Racing Line
4:54 Log Analysis
7:10 Hyperparameters
8:56 Performance Envelope
11:16 The Big Race

✅ RayG's Jupyter Notebook: bit.ly/3msl2Xs
✅ AWS Jupyter Notebooks: bit.ly/33EbJLz
✅ RayG's ML Blog: amzn.to/3jUlSuq
✅ Join the AWS DeepRacer Community: deepracing.io
✅ Learn more about AWS DeepRacer League go.aws/2WKV5Xh
✅ Start racing now!: amzn.to/2UC0Wy4
✅ Watch DeepRacer TV: amzn.to/3aDwjhs
✅ RL E-Course: amzn.to/2UBI4PS
✅ Getting Started Guide: amzn.to/2wWksw8

#AWSDeepRacer #DanielRicciardo #TatianaCalderón #RobSmedley #AWS #DeepRacer #MachineLearning #AutonomousVehicle #ReinforcementLearning #LearnML #fastmachinelearning #MLdeveloper #loganalysis #F1 #RaceAnalytics
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