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GraphLab Create

8
40
+ 1
3
NanoNets

17
47
+ 1
19
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GraphLab Create vs NanoNets: What are the differences?

Developers describe GraphLab Create 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. On the other hand, NanoNets is detailed as "Machine learning API with less data". 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.

GraphLab Create and NanoNets can be categorized as "Machine Learning as a Service" tools.

Some of the features offered by GraphLab Create are:

  • 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.

On the other hand, NanoNets provides the following key features:

  • Image categorization API with less than 30 images per category
  • Custom object localization API
  • Text deduplication API
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Pros of GraphLab Create
Pros of NanoNets
  • 1
    Intelligent Function Defaults
  • 1
    Fast Data Summary
  • 1
    Simple Machine Learning Tools
  • 7
    Simple API
  • 5
    Easy Setup
  • 4
    Easy to use
  • 3
    Fast Training

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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 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.

Need advice about which tool to choose?Ask the StackShare community!

Jobs that mention GraphLab Create and NanoNets as a desired skillset
What companies use GraphLab Create?
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    What tools integrate with GraphLab Create?
    What tools integrate with NanoNets?
      No integrations found

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      What are some alternatives to GraphLab Create and NanoNets?
      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.
      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.
      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.
      See all alternatives