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Azure Machine Learning
Azure Machine Learning

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FloydHub
FloydHub

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Azure Machine Learning vs FloydHub: What are the differences?

Developers describe Azure Machine Learning as "A fully-managed cloud service for predictive analytics". 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. On the other hand, FloydHub is detailed as "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.

Azure Machine Learning and FloydHub belong to "Machine Learning as a Service" category of the tech stack.

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What is 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.

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.
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            What are some alternatives to Azure Machine Learning and FloydHub?
            Python
            Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
            Azure Databricks
            Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.
            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.
            Databricks
            Databricks Unified Analytics Platform, from the original creators of Apache Spark™, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications.
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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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