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API StatusChangelog
Amazon Machine Learning
ByAmazon Machine LearningAmazon Machine Learning

Amazon Machine Learning

#3in Text & Language Models
Discussions1
Followers246
OverviewDiscussions1

What is Amazon Machine Learning?

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 Machine Learning is a tool in the Text & Language Models category of a tech stack.

Key Features

Easily Create Machine Learning ModelsFrom Models to Predictions in SecondsScalable, High Performance Prediction Generation ServiceLow Cost and Efficient

Amazon Machine Learning Pros & Cons

Pros of Amazon Machine Learning

No pros listed yet.

Cons of Amazon Machine Learning

No cons listed yet.

Amazon Machine Learning Alternatives & Comparisons

What are some alternatives to Amazon Machine Learning?

Amazon SageMaker

Amazon SageMaker

A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.

Azure Machine Learning

Azure Machine Learning

Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.

Algorithms.io

Algorithms.io

Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables

Replicate

Replicate

It lets you run machine learning models with a few lines of code, without needing to understand how machine learning works.

Amazon Elastic Inference

Amazon Elastic Inference

Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon.

Google AI Platform

Google AI Platform

Makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively.

Try It

Visit Website

Adoption

On StackShare

Companies
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Amazon Machine Learning Discussions

Discover why developers choose Amazon Machine Learning. Read real-world technical decisions and stack choices from the StackShare community.

Julien DeFrance
Julien DeFrance

Principal Software Engineer at SmartZip

Feb 24, 2019

Needs adviceonServerlessServerlessAWS LambdaAWS LambdaAmazon Machine LearningAmazon Machine Learning

Which #IaaS / #PaaS to chose? Not all #Cloud providers are created equal. As you start to use one or the other, you'll build around very specific services that don't have their equivalent elsewhere.

Back in 2014/2015, this decision I made for SmartZip was a no-brainer and #AWS won. AWS has been a leader, and over the years demonstrated their capacity to innovate, and reducing toil. Like no other.

Year after year, this kept on being confirmed, as they rolled out new (managed) services, got into Serverless with AWS Lambda / #FaaS And allowed domains such as #AI / #MachineLearning to be put into the hands of every developers thanks to Amazon Machine Learning or Amazon SageMaker for instance.

Should you compare with #GCP for instance, it's not quite there yet. Building around these managed services, #AWS allowed me to get my developers on a whole new level. Where they know what's under the hood. Where they know they have these services available and can build around them. Where they care and are responsible for operations and security and deployment of what they've worked on.

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