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Algorithms.io vs Lamina: What are the differences?
Developers describe Algorithms.io as "Machine learning as a service for streaming data from connected devices". Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables. On the other hand, Lamina is detailed as "Artificial Intelligence as an API 🤖". Lamina helps you integrate Deep Learning models like Sentiment Analysis and Entity Extraction into your products with a simple API call. Relieving you of getting data, creating a model and training them which would be compute-intensive.
Algorithms.io and Lamina can be primarily classified as "Machine Learning as a Service" tools.
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What is Algorithms.io?
Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables
What is Lamina?
Lamina helps you integrate Deep Learning models like Sentiment Analysis and Entity Extraction into your products with a simple API call. Relieving you of getting data, creating a model and training them which would be compute-intensive.
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Jobs that mention Algorithms.io and Lamina as a desired skillset
What companies use Algorithms.io?
What companies use Lamina?
What companies use Algorithms.io?
What companies use Lamina?
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What are some alternatives to Algorithms.io and Lamina?
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 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.
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 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
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.