Code360 powered by Coding Ninjas X Naukri.com. Code360 powered by Coding Ninjas X Naukri.com
Table of contents
1.
Introduction
2.
AWS DeepRacer(Race Concept)
3.
Frequently Asked Questions.
3.1.
What is DeepRacer AWS?
3.2.
What is DeepRacer's learning rate?
3.3.
How does DeepRacer work?
3.4.
What is an AWS DeepRacer student?
3.5.
What is an AWS builder?
4.
Conclusion
Last Updated: Mar 27, 2024
Easy

AWS DeepRacer(Race Concept)

Master Python: Predicting weather forecasts
Speaker
Ashwin Goyal
Product Manager @

Introduction

AWS DeepRacer is an integrated learning system that enables users of all levels to learn about reinforcement learning and build self-driving apps. It consists of the following components:

The AWS DeepRacer Console is a machine learning platform for training and testing reinforcement learning models in a simulated autonomous driving environment.

The AWS DeepRacer League is the world's first international independent racing league. Prizes, glory, and a chance to progress to the Championship Cup are all on the line in this race.

AWS DeepRacer(Race Concept)

You've organized a LIVE race and invited participants to participate. With the help of Broadcast a LIVE Community Race using AWS DeepRacer League Production Playbooks, you've determined whether to broadcast your event privately or openly. Now you'll learn how to manage the queue, set up the racing simulator, and send your racers out into the world.

Before you start

  • Use a browser like Chrome or Firefox (Check that your browser is up to date)
  • If you're using a virtual private network (VPN), disconnect it.
  • Close any open tabs.

To run a LIVE virtual race.

  1. Find the race card for the race you wish to moderate on the Community races page and select Join now to see the race.
  2. Choose Launch simulator from the Race organizer control panel on the LIVE: Your Race Name> page. One hour before the start of your race, this button becomes operational. Select the Launch LIVE racing simulator heading to hide this area of the Race organizer control panel.
    
                        Choose the Launch simulator button.

source

  1. To close submissions, turn off Model entries available under COMING UP. Below the toggle, this will close model submissions and establish an editable racer queue. Racers cannot be launched until the toggle is turned off.

                        Toggle off Model entries open to close submissions.

source 

  1. To collect your racers, open the video conference you made.
  2. Begin a racer roll call by saying:
    1. Check with the racers to see whether they can hear you.
    2. To begin, use a video to introduce yourself. To save bandwidth, you might wish to turn it off later.
    3. Make sure the list of participants on the call corresponds to the racers in your group.
  3. Start a mock roll call:
    1. Check that the Racer queue's list of aliases matches those of your racers and that none of them are marked in red, indicating that their model did not successfully submit.
    2. Inquire with your racers to see if they're experiencing any problems submitting their models.
  4. Examine the race schedule as well as the rules. Remind racers that the leaderboard rankings are decided by their single fastest lap during that session.
  5. Explain that the Speed control feature allows the racer to manually set the maximum speed using the speed control slider, which temporarily overrides their model's speed characteristics but not the steering angle. This feature will only be accessible to the racer during their race. The model still steers, but racers may now double the rate to raise or reduce their car's speed at critical periods. Racers can reset the multiplier to 1 to return to utilizing the model's speed settings. Remind racers that the Speed control slider is not a gas pedal but a strategic real-time adjustment option.


                        Racers can use the speed control slider to manually set maximum speed, which temporarily overrides
                            their model’s speed parameters, but not the steering angle.

source

  1. Next, explain that the racing window's video overlay contains data that may be used to improve a racer's performance. The track map overlay is separated into three sectors, each changing color based on the racer's speed. Green shows a racer's personal best, yellow denotes the slowest industry-driven, and purple indicates a session best. Racers will also be able to see information such as their best lap time, remaining time in m/s, resets, and current lap time.
     

                        The track map overlay is divided into three sectors that change color depending on a racer’s pace.
                            Green indicates the section of the tack where a racer clocked a personal best, yellow denotes the
                            slowest sector driven, and purple signifies a session best.

source

  1. Answer racer questions.
  2. Select Edit from the COMING UP menu to reorganize your race queue by dragging and dropping racer names.
     

                        Grab and drop racer names to reorder your race queue.

source

  1. Select Save to maintain your alterations or Cancel to delete them if you make changes to your racing queue.
     

                        Select Save to keep your edits or Cancel to discard them.

source

  1. Start your first racer in the queue:
    1. Select the Launch button next to the top racer queue name to launch each racer manually. After you throw, a "10, 9, 8, 7, 6..." countdown will be animated in the console for each racer's turn.
    2. When you press "Go!" the model will run for the specified period while being assessed in real-time.
    3. You must relaunch the racer using the Launch button next to their alias in the Racer queue if a model fails amid the race.
    4. Contact the next two racers in line through your conference bridge around 2 minutes before the current racer finishes and ensure they are ready to compete.
    5. Give the following racer a 30-second notice 30 seconds before the current racer finishes.
    6. Launch the next racer as soon as you notice that the current racer has completed. A checkered flag icon on the console indicates the finish of the race. The racer's speed control is turned off, and the race is replayed on the video screen.

                        Start an individual racer by selecting their launch button in your racer queue.
  1. If you're having problems with the simulator, you can select to reset it.
  2. If you need to reset the leaderboard for whatever reason, you can click Clear leaderboard ranking, which will remove all entries.
  3. Choose the Declare winner! At the end of your race, Button delivers closing remarks to racers, explains how awards will be divided, and shuts the video conference.
Get the tech career you deserve, faster!
Connect with our expert counsellors to understand how to hack your way to success
User rating 4.7/5
1:1 doubt support
95% placement record
Akash Pal
Senior Software Engineer
326% Hike After Job Bootcamp
Himanshu Gusain
Programmer Analyst
32 LPA After Job Bootcamp
After Job
Bootcamp

Frequently Asked Questions.

What is DeepRacer AWS?

The AWS DeepRacer is a self-driving 1/18th scale race vehicle used to put RL models on a real track through their paces. The car uses cameras to observe the road and a reinforcement model to manage throttle and steering, demonstrating how a model trained in a simulated environment can be applied to the real world.

What is DeepRacer's learning rate?

For smaller batches, the epoch can be insignificant, but for more extensive sets, it can be substantial. The learning rate is the most important of all the hyperparameters. The default learning rate of 0.003 is acceptable, but we may adjust it to meet our needs.

How does DeepRacer work?

AWS DeepRacer uses reinforcement learning to offer the AWS DeepRacer vehicle autonomous driving. You employ a virtual environment with a simulated track to train and analyze a reinforcement learning model. When the training is done, you send the trained model artifacts to your AWS DeepRacer vehicle.

What is an AWS DeepRacer student?

AWS DeepRacer uses reinforcement learning to provide autonomous driving for the AWS DeepRacer vehicle. You use a virtual environment with a simulated track to train and assess a reinforcement learning model. After the training is completed, you submit the trained model artifacts to your AWS DeepRacer car.

What is an AWS builder?

Amazon Web Services (AWS) provides a set of technical, sales, and marketing capabilities to enable software companies in its partner program to connect with new clients and grow their businesses.

Conclusion

So that's the end of the article AWS DeepRacer(Race Concept)

After reading about the AWS DeepRacer(Race Concept), are you not feeling excited to read/explore more articles on the topic of AWS? Don't worry; Coding Ninjas has you covered. 

Upskill yourself in Data Structures and Algorithms, Competitive Programming, JavaScript, System Design, and more with our Coding Ninjas Studio Guided Path! If you want to put your coding skills to the test, check out the mock test series and enter the contests on Coding Ninjas Studio! If you're just getting started and want to know what questions big giants like Amazon, Microsoft, and Uber ask, check the difficultiesinterview experiences, and interview bundle for placement preparations.

However, you may want to pursue our premium courses to give your job an advantage over the competition!

Please vote for our blogs if you find them valuable and exciting.

Happy studying!

Previous article
AWS DeepRacer Part-2
Next article
Building AWS DeepLens Projects
Live masterclass