Project
Reverse Dependencies for numo-narray
The projects listed here declare numo-narray as a runtime or development dependency
0.15
A Ruby-like language for writing Ruby C extensions.
Rubex keeps you happy even when writing C extensions.
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0.14
DICOM is a standard widely used throughout the world to store and transfer medical image data. This library enables efficient and powerful handling of DICOM in Ruby, to the benefit of any student or professional who would like to use their favorite language to process DICOM files and communicate across the network.
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0.12
Time series forecasting for Ruby
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0.12
Simple, powerful data frames for Ruby
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0.12
TensorFlow - the end-to-end machine learning platform - for Ruby
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0.05
A flexible framework for neural network for Ruby
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0.04
Efficient similarity search and clustering for Ruby
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0.04
GR framework - the graphics library for visualisation - for Ruby
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0.03
Cumo is CUDA aware numerical library whose interface is highly compatible with Ruby Numo.
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0.03
FFI wrapper for GDAL/OGR.
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0.02
Edge stream anomaly detection for Ruby
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0.02
Save and load NumPy npy and npz files in Ruby
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0.02
Ruby/Numo - a collection of libraries for numerical computing in Ruby.
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0.02
Numo::GSL development version.
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0.02
Ruby/Numo Linear Algebra library with interface to BLAS/LAPACK.
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0.02
Numpy wrapper for Ruby
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0.02
ruby-dnn is a ruby deep learning library.
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0.02
High performance factorization machines for Ruby
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0.01
Hanny is a Hash-based Approximate Nearest Neighbor (ANN) search library in Ruby.
Hash-based ANN converts vector data into binary codes and builds a hash table by using the binary codes as hash keys.
To build the hash table, Hanny uses Locality Sensitive Hashing (LSH) of approximating cosine similarity.
It is known that if the code length is sufficiently long (ex. greater than 128-bit), LSH can obtain high search performance.
In the experiment, Hanny achieved about twenty times faster search speed than the brute-force search by Euclidean distance.
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0.01
This workbench holds a collection of machine learning
methods in Ruby. Rather than specializing on a single task or method, this
gem aims at providing an encompassing framework for any machine learning
application.
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