I was selected as a 2021 AWS Community Builder for machine learning! The AWS Community Builders program selects participants to help share AWS knowledge and resources to the community through engagements such as blog posts, code, and videos. I was selected for machine learning so you can expect to see some upcoming machine learning on AWS posts. Anyone passionate about AWS is eligible to apply for the program and I encourage you to if you are interested!
AWS has a some fantastic machine learning services for things like natural language processing and image recognition. Amazon SageMaker has come a long way since its initial release. SageMaker supports Tensorflow, PyTorch, and mxnet frameworks. Probably one of the newest services is Amazon SageMaker Feature Store that provides the ability to manage and store features for real-time and batch machine learning pojects.
And let’s not forget the “toys” in the AWS machine learning ecosystem. The AWS DeepLens camera is a great way to get started with things like face recognition and AWS DeepRacer provides an introduction to reinforcement learning by helping your real or virtual car navigate a track. I have experimented with both and while both are a lot of fun they are also highly educational. Thanks to a great open source community it’s even possible to train and evaluate your DeepRacer models locally to avoid AWS spend in case you are a hobbyist on a budget. Then submit your model for competition in the AWS DeepRacer League.
While it’s definitely true that you can get started with machine learning on your own laptop or desktop computer, taking advantage of the features offered by a platform like SageMaker can help reduce the learning curve. The integrations between AWS services makes it easy to connect your data and make it usable from other services in AWS.
So let’s get to building! And while we’re building machines that are learning we will be learning as well!