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NanoNets
NanoNets

12
31
+ 1
15
wise.io
wise.io

1
6
+ 1
0
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NanoNets vs wise.io: What are the differences?

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; wise.io: Machine Learning as a Service and Big Data Analytics. Wise.io builds machine intelligence products that make it easy for companies to derive actionable insight from their greatest corporate resource: their data.

NanoNets and wise.io belong to "Machine Learning as a Service" category of the tech stack.

Some of the features offered by NanoNets are:

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

On the other hand, wise.io provides the following key features:

  • Use Wise.io for: Fraud detection, Intelligent sensors, Ad Targeting & Personalization, Genomics, Business Analytics, Finance, Healthcare, Sentiment Analysis
  • Dead simple machine learning.- Our intuitive, easy-to-use platform for machine learning enables anyone to build and deploy models with a few simple clicks.
  • A data science marketplace.- With the feature marketplace, we provide companies access to an expansive knowledge base.
- No public GitHub repository available -
- No public GitHub repository available -

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.

What is wise.io?

Wise.io builds machine intelligence products that make it easy for companies to derive actionable insight from their greatest corporate resource: their data.
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            What are some alternatives to NanoNets and wise.io?
            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.
            Algorithms.io
            Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables
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