Amazon Machine Learning vs Paperspace

Amazon Machine Learning vs Paperspace: 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; Paperspace: The way to access and manage limitless computing power in the cloud. It is a high-performance cloud computing and ML development platform for building, training and deploying machine learning models. Tens of thousands of individuals, startups and enterprises use it to iterate faster and collaborate on intelligent, real-time prediction engines.

Amazon Machine Learning and Paperspace 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, Paperspace provides the following key features:

• Intelligent alert
• Two-factor authentication
• Share drives