9. Machine learning tools: Apache Spark MLlib and Singa
Apache Spark MLlib is an in-memory data processing framework. Spark offers a large and growing library of useful algorithms and utilities incorporating classification, regression, clustering, collaborative filtering and more (for in-memory data processing).
Singa is an open source framework within the Apache incubator, providing a programming tool for deep-learning networks across numerous machines.
10. Machine learning tools: Veles
Veles is Samsung's distributed deep learning platform, which is written in C++ and uses Python for coordination between nodes. Veles offers an API enabling immediate use of trained models and can be used for data analysis.
11. Machine learning tools: Alibaba's Aliyun
In August 2015, Chinese ecommerce giant Alibaba announced that its cloud computing business, Aliyun, would offer a machine learning service to help enterprise customers streamline analytics software development.
The service is based on Aliyun's Open Data Processing Service (ODPS) technology, which is capable of processing 100 petabytes of data in six hours.
The DT PAI platform offers a drag and drop interface to simplify the process for developers.
"What used to take days can be completed in minutes," said Xiao Wei, senior product expert with Alibaba's cloud business, as the service was announced.
12. Machine learning tools: Caffe
Caffe is a deep learning C++ framework initially created for machine vision uses (an imaging-based automatic inspection). It is developed by the Berkeley Vision and Learning Center (BVLC) as well as community developers.
The framework is already used as part of "academic research projects, startup prototypes, and even large-scale industrial applications in vision, speech, and multimedia".
Yahoo recently open sourced CaffeOnSpark, combining deep learning functionality with the Spark data processing engine.
Google and Pintrest have also used Caffe in their operations.
13. Machine learning tools: Neon
Neon is Nervana's open source, Python-based machine learning library.
The deep learning startup, founded in 2014, has also launched a cloud service based on Neon, which it claims is ten times faster than competing services. This means that businesses can build, train and deploy deep-learning technologies much more quickly.
14. Machine learning tools: Wise.io
Wise.io also aims to democratise the use of artificial intelligence with 'machine learning as a service' that is ready for enterprise use. Founded in 2012, the Californian startup's algorithms were initially developed to help astronomers discover and map new stars, before being put to use by businesses.
Its customers include Volkswagen and Citrix.
Source: Computerworld UK
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