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MXNet
 
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Deep Learning Software
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June 15, 2017

Microsoft Cognitive Toolkit

The Microsoft Cognitive Toolkit is a free, easy-to-use, open-source, commercial-grade toolkit that trains deep learning algorithms to learn like the human brain. The Microsoft Cognitive Toolkit—previously known as CNTK—empowers users to harness the intelligence within massive datasets through deep learning by providing uncompromised scaling, speed, and accuracy with commercial-grade quality and compatibility with the programming languages and algorithms users already use. The Microsoft Cognitive Toolkit, is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph. In this directed graph, leaf [...]

67.75
 
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June 15, 2017

MXNet

Mxnet is a flexible and efficient library for deep learning. MXNet is developed by collaborators from multiple universities and companies. MXNet provides a rich Python API to serve a broad community of Python developers. MXNet offer powerful tools to help developers exploit the full capabilities of GPUs and cloud computing. While these tools are generally useful and applicable to any mathematical computation, MXNet places a special emphasis on speeding up the development and deployment of large-scale deep neural networks. With MXNet, it’s easy to specify where each data structures should live. MXNet makes it easy to scale computation with number of [...]

18.5
 
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June 15, 2017

Apache SINGA

Apache SINGA is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.SINGA’s software stack includes three major components, namely, core, IO and model. Figure 1 illustrates these components together [...]

20.75
 
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June 15, 2017

ND4J

ND4J is a scientific computing libraries for the JVM. It is meant to be used in production environments, which means routines are designed to run fast with minimum RAM requirements. ND4J is used by national laboratories for tasks such as climatic modeling, which require computationally intensive simulations. ND4J brings the intuitive scientific computing tools of the Python community to the JVM in an open source, distributed and GPU-enabled library. In structure, it is similar to SLF4J. ND4J gives engineers in production environments an easy way to port their algorithms and interface with other libraries in the Java and Scala ecosystems. ND4J is also an [...]

10.75
 
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June 15, 2017

Gensim

Gensim is a FREE Python library that has scalable statistical semantics. It analyzes plain-text documents for semantic structure and retrieve semantically similar documents. In addition, Gensim is a robust, efficient and hassle-free piece of software to realize unsupervised semantic modelling from plain text. It stands in contrast to brittle homework-assignment-implementations that do not scale on one hand, and robust java-esque projects that take forever just to run “hello world”. Gensim is licensed under the OSI-approved GNU LGPLv2.1 license. This means that it’s free for both personal and commercial use, but if users make any modification to gensim [...]

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