DeepRacer League logo

Pit Stop

Welcome to the AWS DeepRacer Pit Stop, where developers of all skill levels can share and pick up some racing tips from the AWS DeepRacer community. Find the most up to date resources and advice from our experts on how to tune models to improve lap times, and share racing strategy with racers from around the world.


Connect with the Community

Ask questions, exchange tips, and share best practices with fellow racers.

Check out other AWS DeepRacer resources including the AWS DeepRacer Reddit community and AWS re:Post.

2020 AWS DeepRacer re:Invent Sessions

Watch the 2020 re:Invent sessions on-demand to quickly learn how to make your way to the podium.

200L: Get rolling with machine learning
Get hands-on experience with AWS DeepRacer and build your first model.
300L: AWS DeepRacer analysis tools
Explore how human analysis of reinforcement learning through logs improves your racing performance
400L: Conquer the track with SageMaker
Dive into SageMaker notebooks to learn how you can apply your reinforcement learning models to relevant use cases.
60-second tips to learn machine learning

Learn quick tips about machine learning such as the model building process and the action space.

Reaching Convergence
Learn about the importance of convergence in the model building process.
Defining Action Space
Learn about action space from our AWS DeepRacer TV host Blaine Sundrud.
Learn about the benefits and drawbacks of overfitting an AWS DeepRacer model.
Log analysis tool
Use this tool to help you debug and improve your model's driving performance »
Tutorials to help you with your racing performance
Map out your machine learning journey with waypoints.
Variable future waypoints
Help your model keep an eye on the road with variable future waypoints.
Getting Started Resources

Whether you are new to machine learning or ready to build on your existing skills, we can help you get ready to race.

AWS DeepRacer Expert Bootcamps from re:Invent 2019

Deep dive with AWS DeepRacer experts on techniques to test your first model.

Tune Hyperparameters
Learn how to tune hyperparameters in Amazon SageMaker with Guy Ernest.
Defining Action Space
From sim to reality: how to design & test your model for the real world with Ray Goh.
DeepRacer Community
Learn how you can join the global online AWS DeepRacer community:
Model interpretability
Explore techniques to visualize where the DeepRacer RL model chooses to focus.
Official Merchandise Store
Score exclusive AWS DeepRacer apparel in the track store

AWS DeepRacer TV

AWS DeepRacer TV follows the world’s first global autonomous racing league, featuring developers of all skill levels as they progress their machine learning skills. Tune in to follow the journey as F1 professionals Daniel Ricciardo, Tatiana Calderón, and Rob Smedley as they face off against first time and expert ML developers alike all hoping to qualify for a chance to win the Championship Cup at AWS re:Invent.

Watch the series »

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 the pros during Grand Prix.


See the drama unfold in episode 6 as 64 of the world's best AWS DeepRacer developers face off in the re:Invent Championship Cup knockout rounds.
Season one ends with a bang as the field of 64 finalists is winnowed down to crown the 2019 champion.
Learn more about pricing

Information on AWS DeepRacer pricing and integration with other AWS services.

Learn more 
AWS DeepRacer League Rules

Information on AWS DeepRacer League rules and eligibility requirements.

View the Rules 
Order your AWS DeepRacer

Get hands-on with RL, experiment, and learn through autonomous driving.

Buy now