1. AWS Data Pipeline is a cloud-based data workflow service that helps you process and move data between different AWS services and on-premise.

  2. A blog written by Apple engineers

  3. scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

  4. Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

    freemium

  5. Build and train machine learning models with Google

  6. A curated collection of machine learning projects

  7. Fully managed extract, transform, and load (ETL) service

  8. Machine learning made easy for developers of any skill level

  9. Coralogix is a machine learning powered log analytics solution aimed to solve the problem of unmanageable log data.

  10. TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

  11. A serverless platform for building event-based microservices.

  12. Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.


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This article was published on | Author: | Publisher: SaaSHub
Categories: Data Science And Machine Learning, ETL, Big Data Tools