Get Advice Icon

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

GraphLab Create
GraphLab Create

3
7
+ 1
3
NanoNets
NanoNets

12
31
+ 1
15
Add tool

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
- No public GitHub repository available -
- No public GitHub repository available -

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.
Get Advice Icon

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

Why do developers choose GraphLab Create?
Why do developers choose NanoNets?
    Be the first to leave a con
      Be the first to leave a con
      What companies use GraphLab Create?
      What companies use NanoNets?
        No companies found

        Sign up to get full access to all the companiesMake informed product decisions

        What tools integrate with GraphLab Create?
        What tools integrate with NanoNets?
          No integrations found

          Sign up to get full access to all the tool integrationsMake informed product decisions

          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.
          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.
          See all alternatives
          Decisions about GraphLab Create and NanoNets
          No stack decisions found
          Interest over time
          Reviews of GraphLab Create and NanoNets
          No reviews found
          How developers use GraphLab Create and NanoNets
          No items found
          How much does GraphLab Create cost?
          How much does NanoNets cost?
          Pricing unavailable
          News about GraphLab Create
          More news