AWS Machine Learning

AWS Machine learning now includes 25 distinct products/services. This makes it one of the most robust areas within the AWS ecosystem, with more complexity and continued development then both the AWS Compute and Storage services areas combined.

At Metal Toad, areas of Machine Learning expertise include a top three list (in order of how awesome we think they are):

Amazon Rekognition
Amazon SageMaker
Amazon Comprehend

#1 Amazon Rekognition

A trainable visual machine learning algorithm, Rekognition can be used for face identification or trained to be able to identify all kinds visual objects. A cloud-based competitor to the open source YOLO (You Only Look Once) Python project, Rekognition's cloud-based nature means that it is growing and improving all the time. It's amazing to work with and a ton of fun. You can watch the latest rollout of features from re:Invent below:

#2 Amazon SageMaker

SageMaker is AWS's core machine learning platform - the thing that takes big data and turns into business intelligence, with the right training of course. Machine Learning is unlike most programming scenarios in that you actually aren't writing code, but rather setting the algorithm lose to do it for you. With several certified AWS Machine Learning team members on staff, SageMaker is regularly being introduced in both customer projects and Metal Toad hack-a-thons.

#3 Amazon Comprehend

Amazon Comprehend is truly machine learning on a grandiose scale. Comprehend is a fully managed natural language processing service that analyzes deduces human expression in text in a totally unique way. For instance, you could feed it the comments on your org’s Facebook page and run a sentiment analysis to understand instantly how people feel about your brand—the ultimate data-validated gut check. See it's rollout way back in 2017 by Andy Jassy at re:Invent: