Get Advice Icon

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

BigML
BigML

6
4
+ 1
1
NanoNets
NanoNets

12
31
+ 1
15
Add tool

BigML vs NanoNets: What are the differences?

BigML: Machine Learning, made simple. Predictive analytics for big data and not-so-big data. BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services; NanoNets: 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.

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

Some of the features offered by BigML are:

  • REST API
  • bindings in Pyton, Java, Ruby, node.js, C#, Clojure, PHP, and more
  • several algorithms, including categorical & regression decision trees, ensembles of trees (random decision forest), cluster analysis and more

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 BigML?

BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.

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 BigML?
Why do developers choose NanoNets?
    Be the first to leave a con
      Be the first to leave a con
      What companies use BigML?
      What companies use NanoNets?

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

      What tools integrate with BigML?
      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 BigML and NanoNets?
        DataRobot
        It is an enterprise-grade predictive analysis software for business analysts, data scientists, executives, and IT professionals. It analyzes numerous innovative machine learning algorithms to establish, implement, and build bespoke predictive models for each situation.
        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 BigML and NanoNets
        No stack decisions found
        Interest over time
        Reviews of BigML and NanoNets
        No reviews found
        How developers use BigML and NanoNets
        No items found
        How much does BigML cost?
        How much does NanoNets cost?
        News about BigML
        More news