Amazon Personalize vs Aquarium: What are the differences?

Amazon Personalize: Real-time personalization and recommendation. Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications; Aquarium: *Improve Your ML Dataset Quality *. Machine learning models are only as good as the datasets they're trained on It helps ML teams make better models by improving their dataset quality..

Amazon Personalize can be classified as a tool in the "Machine Learning as a Service" category, while Aquarium is grouped under "Machine Learning Tools".

Some of the features offered by Amazon Personalize are:

• Combine customer and contextual data to generate high-quality recommendations
• Automated machine learning
• Continuous learning to improve performance

On the other hand, Aquarium provides the following key features:

• Upload your dataset to get a health check of its quality, quantity, and diversity. Zoom in and out of your dataset. Uncover distribution biases before you train. Find and fix labeling errors quickly
• Upload model inferences against your labeled datasets and deep dive into its performance. Find where your model is performing well and badly so you can take the best actions to improve it
• With knowledge of your dataset diversity and model performance, it automatically samples the best data to sample to label and retrain on. Your model performance just gets better