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Gradient°
Gradient°

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GraphLab Create
GraphLab Create

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Gradient° vs GraphLab Create: What are the differences?

Developers describe Gradient° as "Deep learning platform built for developers". Gradient° is a suite of tools for exploring data and training neural networks. Gradient° includes 1-click Jupyter notebooks, a powerful job runner, and a python module to run any code on a fully managed GPU cluster in the cloud. Gradient is also rolling out full support for Google's new TPUv2 accelerator to power even more newer workflows. On the other hand, GraphLab Create is detailed as "Machine learning platform that enables data scientists and app developers to easily create intelligent apps at scale". Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.

Gradient° and GraphLab Create can be primarily classified as "Machine Learning as a Service" tools.

Some of the features offered by Gradient° are:

  • 1-click Jupyter notebooks
  • a powerful job runner
  • Python module to run any code on a fully managed GPU cluster in the cloud

On the other hand, GraphLab Create provides the following key features:

  • Analyze terabyte scale data at interactive speeds, on your desktop.
  • A Single platform for tabular data, graphs, text, and images.
  • State of the art machine learning algorithms including deep learning, boosted trees, and factorization machines.
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- No public GitHub repository available -

What is Gradient°?

Gradient° is a suite of tools for exploring data and training neural networks. Gradient° includes 1-click Jupyter notebooks, a powerful job runner, and a python module to run any code on a fully managed GPU cluster in the cloud. Gradient is also rolling out full support for Google's new TPUv2 accelerator to power even more newer workflows.

What is GraphLab Create?

Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.
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              What are some alternatives to Gradient° and GraphLab Create?
              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.
              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.
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