What AWS service would you use for image and video processing with machine learning capabilities?

Amazon Rekognition is the correct choice for image and video processing with machine learning capabilities because it is specifically designed for analyzing visual content. This fully managed service uses deep learning models to identify objects, people, scenes, and activities in images and videos. It offers features such as facial analysis (emotion detection, age estimation), object and scene detection, and can even recognize celebrities, making it a versatile tool for various applications involving visual media.

Amazon SageMaker, while powerful for building, training, and deploying machine learning models, does not focus on image and video processing as its primary use case. It provides tools for model creation but does not inherently include the ready-to-use functionalities for analyzing images or videos like Rekognition does.

Amazon DeepLens is a hardware device used for running deep learning models at the edge. While it can be used to process images and videos, it requires designing and deploying models, which may necessitate additional engineering and complexity beyond just simple image and video analysis.

Amazon Elastic Transcoder is primarily a media transcoding service. It is used for converting media files from one format to another, which is a different function than leveraging machine learning for analysis or processing of images and videos.

Therefore, Amazon Rekognition stands out as the service specifically tailored for