12
31
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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.
NanoNets is a tool in the Machine Learning as a Service category of a tech stack.

Who uses NanoNets?

Companies
3 companies reportedly use NanoNets in their tech stacks, including GridAnts, Indra, and ULC Robotics.

Developers
8 developers on StackShare have stated that they use NanoNets.

NanoNets Integrations

PHP, Node.js, Python, Postman, and Ruby are some of the popular tools that integrate with NanoNets. Here's a list of all 10 tools that integrate with NanoNets.

Why developers like NanoNets?

Here’s a list of reasons why companies and developers use NanoNets
Top Reasons

NanoNets's Features

  • Image categorization API with less than 30 images per category
  • Custom object localization API
  • Text deduplication API
  • Text categorization API

NanoNets Alternatives & Comparisons

What are some alternatives to NanoNets?
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.
Amazon Elastic Inference
Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon.
FloydHub
Platform-as-a-Service for training and deploying your DL models in the cloud. Start running your first project in < 30 sec! Floyd takes care of the grunt work so you can focus on the core of your problem.
See all alternatives

NanoNets's Followers
31 developers follow NanoNets to keep up with related blogs and decisions.
Mohamma76685757
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Nicolas Marshall
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