Amazon Personalize vs Google AutoML Tables: 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; Google AutoML Tables: Automatically build and deploy machine learning models on structured data. Enables your entire team of data scientists, analysts, and developers to automatically build and deploy machine learning models on structured data at massively increased speed and scale.

Amazon Personalize can be classified as a tool in the "Machine Learning as a Service" category, while Google AutoML Tables 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, Google AutoML Tables provides the following key features:

• Increases model quality
• Easy to build models
• Easy to deploy