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Amazon Personalize
Amazon Personalize

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wise.io
wise.io

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Amazon Personalize vs wise.io: What are the differences?

What is Amazon Personalize? Real-time personalization and recommendation. Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications.

What is 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.

Amazon Personalize and wise.io can be categorized as "Machine Learning as a Service" tools.

Some of the features offered by Amazon Personalize are:

  • Combine customer and contextual data to generate high-quality recommendations
  • Automated machine learning
  • Continuous learning to improve performance

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 Amazon Personalize?

Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications.

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 Amazon Personalize and wise.io?
                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.
                Keras
                Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
                scikit-learn
                scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
                PyTorch
                PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
                ML Kit
                ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
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