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King, D. E. Dlib-ml: A machine learning toolkit.
The machine learning toolkit is great at this.
It provides PILOT, a machine learning toolkit that is particularly designed to work with streaming interfaces.
The new version further develops astroML into a general machine learning toolkit for the next generation of astrophysical surveys.
To tackle those challenges, we developed a framework which allows users to perform exploratory model analysis based on the hardware accelerated machine learning toolkit BIDMach.
The implemented system has a hybrid architecture of using Spark or Hive for big data processing, and using the machine learning toolkit, MADlib, for doing in-database data analytics in PostgreSQL database.
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Google, Facebook, and Microsoft have recently released machine learning toolkits to the world.
ML libraries and frameworks will be discussed in the "Machine learning toolkits" and "Evaluation of machine learning tools" sections.
Popular machine learning toolkits such as R [3] or Weka [4] were not built for these kinds of workloads.
"Machine learning toolkits" discusses criteria for evaluation of machine learning tools and libraries, and "Evaluation of machine learning tools" provides an in-depth analysis of specific frameworks that can be used with the processing platforms.
A variety of machine learning toolkits have been created to facilitate the learning process but many researchers and practitioners reject them for various reasons, most often because they lack needed features or are difficult to integrate into an existing environment.
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