A data analyst’s life is a journey of continuous learning. However, this can be daunting and has led to the working Millenials come to be known as The Burnout Generation.
To avoid such situations, especially in data analytics, these techies regularly participate in different competitions moderated by different blue-chip companies, such as the coveted AWS DeepRacer challenge.
What is AWS DeepRacer?
AWS DeepRacer is a platform where one can learn and build autonomous driving applications by leveraging deep learning. Deep learning enthusiasts can build models and deploy their DeepRacer vehicle on various tracks for a race.
While one can take part in a physical competition organised by AWS at several locations around the world, you can also compete in virtual environments. To differentiate participants from simulated and physical tracks, AWS has different leagues: virtual and physical leaderboards.
In virtual leaderboard, one can submit trained reinforcement learning model to check how efficient their model is against competitors. People from different countries compete in this, thereby, one can evaluate their capabilities in machine learning.
What will you do?
Primarily, you will have to train your AWS car that is powered by Intel Atom™ on the track through reinforcement learning. The vehicle is equipped with 4 MP camera, 4 GB RAM, 32 Gb storage, and integrated sensors. By using several reinforcement learning techniques, you will have to improve on the lap timing of your car. Further, you can submit your model that delivered the best time to the leaderboard. To keep decreasing your lap time, you need to train your vehicle repeatedly by manipulating parameters.
However, with the free version, you will only get a few hours to train the vehicle, which will be renewed every month, so randomly altering parameters will not be sufficient. Be wise and ensure you have done your research before changing and training the model again.
Inside AWS DeepRacer
The AWS DeepRacer is an integrated learning platform, which can be utilised to train and evaluate with the help of the graphical interface, DeepRacer Console. One can get started by creating a model by tuning hyperparameters, defining reward functions, action space of the vehicle, and select a track to train. Eventually, you will evaluate the performance of your agent and try to enhance its performance by training, all the while tuning parameters of the reinforcement learning model.
How to participate
AWS is making great strides in cloud computing, thus staying abreast of the platforms will only be another feather in the cap of professionals. Getting started with DeepRacer shall enable you to familiarise with the AWS platform. While you will build, train, and race, exploring the platform for it’s behind the scene structure will enhance your understanding of how AWS handles various processes.
The whole fabric of the AWS DeepRacer is managed by Amazon SageMaker, AWS RobotMaker, Amazon S3, Amazon CloudWatch, and more. Thus, one can binge learn many technologies, and later on leverage them in several projects.
AWS DeepRacer is arguably one of the best ways to learn while getting hands-on practice in reinforcement learning. Besides, the leaderboard further encourages you to continuously learn and rise above other competitors, thereby, motivating you to enhance your skills. The AWS DeepRacer site has useful information to get started and learn the technicality of reinforcement learning. Further, they also have an engaging community that can assist you in getting answers to your query. Altogether it is an exceptional platform to learn while having fun, resulting in provoking you to master machine learning.
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