Amazon Machine Learning vs Amazon Personalize: What are the differences?
Amazon Machine Learning: Visualization tools and wizards that guide you through the process of creating ML models w/o having to learn complex ML algorithms & technology. This new AWS service helps you to use all of that data you’ve been collecting to improve the quality of your decisions. You can build and fine-tune predictive models using large amounts of data, and then use Amazon Machine Learning to make predictions (in batch mode or in real-time) at scale. You can benefit from machine learning even if you don’t have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure; 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.
Amazon Machine Learning and Amazon Personalize can be primarily classified as "Machine Learning as a Service" tools.
Some of the features offered by Amazon Machine Learning are:
- Easily Create Machine Learning Models
- From Models to Predictions in Seconds
- Scalable, High Performance Prediction Generation Service
On the other hand, Amazon Personalize provides the following key features:
- Combine customer and contextual data to generate high-quality recommendations
- Automated machine learning
- Continuous learning to improve performance
What is Amazon Machine Learning?
What is Amazon Personalize?
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Why do developers choose Amazon Machine Learning?
Why do developers choose Amazon Personalize?
What are the cons of using Amazon Machine Learning?
What are the cons of using Amazon Personalize?
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What tools integrate with Amazon Machine Learning?
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