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GraphLab Create

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Turi Create

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GraphLab Create vs Turi Create: What are the differences?

Key Differences Between GraphLab Create and Turi Create

GraphLab Create and Turi Create are both machine learning platforms developed by Turi (formerly known as Dato and GraphLab). While both platforms provide tools for building and deploying machine learning models, there are several key differences between them.

  1. Licensing Model: GraphLab Create uses a commercial, proprietary license, which means it requires a paid subscription to use. On the other hand, Turi Create is an open-source library, released under the Apache 2.0 license, making it free for anyone to use and modify.

  2. Accessibility: GraphLab Create is a commercial product with a paid subscription, so it provides dedicated customer support, documentation, and additional resources to subscribers. Turi Create, being an open-source library, relies on community support and resources, which may be more limited compared to GraphLab Create.

  3. Integration with Other Libraries: Turi Create integrates well with other popular Python libraries such as NumPy, Pandas, and TensorFlow. This allows users to leverage the functionalities of these libraries along with Turi Create's machine learning capabilities seamlessly. GraphLab Create, on the other hand, is a more self-contained platform that may not have the same level of integration with other libraries.

  4. Model Deployment: GraphLab Create offers more options for deploying machine learning models. It provides features like server deployment, which allows users to create RESTful APIs for prediction serving. Turi Create, being an open-source library, does not have the same out-of-the-box deployment options, although it still provides ways to export trained models for inference.

  5. Supported Algorithms: Turi Create focuses on providing a simplified interface to a limited set of machine learning algorithms. This makes it easier for novice users to start with machine learning but may limit the flexibility for advanced users. GraphLab Create, being a more mature and commercial product, offers a wider range of algorithms and advanced techniques for machine learning tasks.

  6. Development Stage: GraphLab Create has been around for longer and has a more established user base. It is a more mature and stable platform compared to Turi Create, which is a relatively newer open-source project. While Turi Create is actively maintained and developed, it may have some limitations and rough edges compared to GraphLab Create.

In summary, GraphLab Create is a commercial platform with a proprietary license, providing dedicated support, and a wider range of algorithms, while Turi Create is an open-source library with more limited support options but with a focus on simplicity and ease of use.

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Pros of GraphLab Create
Pros of Turi Create
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    Intelligent Function Defaults
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    Fast Data Summary
  • 1
    Simple Machine Learning Tools
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    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.

    What is Turi Create?

    It simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app.

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      What are some alternatives to GraphLab Create and Turi Create?
      scikit-learn
      scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
      TensorFlow
      TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
      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.
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