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FloydHub
FloydHub

6
7
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0
wise.io
wise.io

1
6
+ 1
0
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FloydHub vs wise.io: What are the differences?

FloydHub: Heroku for Deep Learning. Platform-as-a-Service for training and deploying your DL models in the cloud. Start running your first project in < 30 sec! Floyd takes care of the grunt work so you can focus on the core of your problem; wise.io: Machine Learning as a Service and Big Data Analytics. Wise.io builds machine intelligence products that make it easy for companies to derive actionable insight from their greatest corporate resource: their data.

FloydHub and wise.io can be primarily classified as "Machine Learning as a Service" tools.

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What is FloydHub?

Platform-as-a-Service for training and deploying your DL models in the cloud. Start running your first project in < 30 sec! Floyd takes care of the grunt work so you can focus on the core of your problem.

What is wise.io?

Wise.io builds machine intelligence products that make it easy for companies to derive actionable insight from their greatest corporate resource: their data.
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                What are some alternatives to FloydHub and wise.io?
                Paperspace
                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.
                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 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.
                NanoNets
                Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.
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                Avatar of Mark Melnykowycz
                Mark Melnykowycz uses FloydHubFloydHub

                Easy way to scale data science projects from laptop to the cloud to utilize GPU processing power and access key data training sets without downloading to your local machine.

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