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Machine learning platform that enables data scientists and app developers to easily create intelligent apps at scale

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.
GraphLab Create is a tool in the Machine Learning as a Service category of a tech stack.

Who uses GraphLab Create?

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Why developers like GraphLab Create?

Here’s a list of reasons why companies and developers use GraphLab Create

GraphLab Create's 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.
  • Run the same code on your laptop or in a distributed system, using a Hadoop Yarn or EC2 cluster.
  • Focus on tasks or machine learning with the flexible API.
  • Easily deploy data products in the cloud using Predictive Services.
  • Visualize data for exploration and production monitoring.

GraphLab Create Alternatives & Comparisons

What are some alternatives to GraphLab Create?
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
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.
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.
See all alternatives

GraphLab Create's Stats

- No public GitHub repository available -